x-xEPA
United States
Environmental Pro tec lion
Agency
Office of
Noise Abatement and Control
Washington, D.C. 20460
EPA 550/9-79-102
November 1979
Noise
Comparison of Various
Methods for Predicting
the Loudness
and Acceptability of Noise
Part II:
Effects of Spectral
Pattern and Tonal
Components
LOUDNESS
LEVEL (PHON)
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COMPARISON OF VARIOUS METHODS
FOR PREDICTING THE LOUDNESS AND
ACCEPTABILITY OF NOISE
Part II
EFFECTS OF SPECTRAL PATTERN
AND TONAL COMPONENTS
November 1979
Prepared by
B. Scharf and R. Hellman
Auditory Perception Laboratory
Northeastern University
Boston, Massachusetts 02115
Prepared for
U.S. Environmental Protection Agency
Office of Noise Abatement and Control
Washington, D.C. 20460
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PREFACE
The United States Environmental Protection Agency (EPA) was charged
by Congress in the Noise Control Act of 1972, as amended by the Quiet
Communities Act of 1978, to conduct or finance research to investigate
"...the psychological and physiological effects of noise on humans and the
effects of noise on domestic animals, wildlife, and property, and the deter-
mination of dose/response relationships suitable for use in decision making..."
(Section 14(b)(l)).
Pursuant to and as part of this mandate, EPA has undertaken investi-
gations to determine and quantify subjective reactions of individuals and
communities to different noise environments and sources of noise. A specific
series of studies has been initiated to determine the best methods for eval-
uating subjective magnitude and aversiveness to noise on the basis of spectral
and temporal properties, and to ascertain the importance of and means for
including nonacoustical factors in the evaluation of general aversion to noise.
The overall purpose of this line of research.is to derive a more solid basis
for assessing the aversiveness of noise and the benefits of noise control.
The program calls for detailed analysis and evaluation of available data from
both the laboratory and the field to assess the relative validity and pre-
dictiveness of various subjective acoustic ratings (spectral weightings and
calculation schemes), as well as to acquire new data where appropriate.
Findings have been published previously in EPA Report No. 550/9-77-101
entitled "Comparison of Various Methods for Predicting the Loudness and
Acceptability of Noise." That report dealt with the ability of commonly
employed frequency weightings and calculation schemes to predict and quantify
subjective aspects of sound. The results of the study showed the calculation
schemes to be superior in predictive capability to the frequency weightings.
111
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The D- and E-frequency weightings were significantly better than the B- and
C-weightings. The A-weighting was only slightly more variable than the D-
and E-weightings. All frequency weightings were level dependent with the
predictive capability worse at higher levels. Analysis of the results with
regard to the type of noise and the presence of tonal components was not
conclusive due to a limited amount of available data.
The purpose of the investigation described in this report was to under-
take a more detailed, rigorous, and systematic analysis of the previously
compiled psychoacoustic data in order to (a) account for certain apparent
anomalies in the data analyzed earlier as part of this program, (b) examine
the sensitivity of various frequency weightings and rating schemes to spectral
differences of the sound stimuli used in the investigations, and (c) evaluate
subjective response to discrete frequency components superimposed over a back-
ground. The results provide partial but needed information on the relative
ability of computational procedures and frequency weightings to assess sub-
jective loudness and acceptability of sounds with different spectral shapes,
the necessity of tonal corrections at low and high levels of noise, an indi-
cation as to the magnitude of a correction, and the overall effectiveness of
commonly used tonal correction procedures.
EPA believes that further evaluation of data on the subjective effects
of noise will foster the development of techniques to demonstrate additional
benefits of noise control beyond that exhibited by currently used procedures.
Fulfillment of this objective awaits further study within this series. The
results published in this report, however, do provide an important step to-
ward a more complete understanding of the phenomena of human subjective
response to noise.
OFFICE OF THE SCIENTIFIC ASSISTANT
TO THE DEPUTY ASSISTANT ADMINISTRATOR
OFFICE OF NOISE ABATEMENT AND CONTROL
U.S. ENVIRONMENTAL PROTECTION AGENCY
iv
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Abstract
The present report is a continuation of an earlier report by Scharf,
Hellman, and Bauer (1977). The objectives are (1) to determine whether sub-
jective judgments of particular types of noise, categorized by spectral
shape, are better approximated by some descriptors (frequency weightings and
calculation procedures) than by others, and (2) to investigate the role of
tonal components in these studies and to assess the adequacy of several
tone-correction procedures. The analysis of data by spectral shape produced
a mixed outcome. Results showed that no overall advantage would accrue
from regrouping sets of data across studies on the basis of similar spectral
shapes. However, although variability was not reduced when considered
across nine spectral categories, the interaction between spectral shape
and descriptor was highly significant (p < .001). The examination of over
500 spectra with and without tonal components provided only tentative
support for the trends noted in the literature. When the judged attribute is
either loudness or noisiness, tonal components do not seem to add to the
subjective magnitude of broad-band noise below 80 dB sound pressure level.
At higher levels, according to one large-scale study, tonal components
seemed to add the equivalent of 2 dB to the judged noisiness. No data could
be located that would permit adequate assessment of the contribution of tonal
components to the "absolute" magnitude of judged annoyance or unacceptability
(as distinct from noisiness or loudness). Given the small effect of tonal
components in the present group of studies, the evaluation of three different
tone-correction procedures (FAR 36, 1969; Kryter and Pearson's, 1965;
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and Stevens's, 1970) could not lead to definitive conclusions about their
relative merits. Although a small correction may be necessary for the
presence of tonal components at high levels, the tone-correction procedures
now available cannot be properly evaluated until more appropriate data that
demonstrate the need for a tone correction are obtained.
VI
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ACKNOWLEDGEMENTS
We thank Professor Merv Lynch for his aid in statistical analyses,
Barbara Kane for implementing the ANOVA programs on the computer, and
Harvey Branscomb for writing programs to handle the various tone-correc-
tion procedures. We also wish to express our thanks to Jeffrey Goldstein,
project director at EPA, for his constructive reviews of initial drafts of
this report. A number of undergraduate and graduate students at North-
eastern University also helped us with the many details of this report;
they include Eleanor Arpino, Angela Ashton, Maureen Hogan, Tom Horton,
and Patricia Moran. Correspondence and most of the typing were beauti-
fully handled by Ana Silfer.
VII
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vm
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TABLE OF CONTENTS
Page
I. INTRODUCTION 1
II. SPECTRAL SHAPE 3
III. TONAL COMPONENTS 21
1. Composition of Studies with Respect to Tonal Components 24
2. Evidence Demonstrating a Need for a Tone Correction 24
3. Descriptions of Tone-Correction Procedures 37
a) PNLC or FAR 36 Tone Corrections 37
b) Kryter and Pearsons°s (1965) Tone-Correction Procedure 38
c) Stevens's (1970) Preliminary Tone-Correction Procedure 40
4. Other Tone-Correction Procedures 44
5. Evaluation of Tone-Correction Procedures 45
a) Variability 45
b) Mean Differences Between Calculated and Observed Levels 48
6. Summary of Findings Relative to Tonal Components 52
IV. CONCLUSIONS AND RECOMMENDATIONS 53
APPENDICES
A. CATEGORICAL ANALYSIS ACCORDING TO SPECTRAL TYPE A-l
B. "ANOMALOUS" DATA B-l
C. STEVENS'S TONE-CORRECTION - 1970 PRELIMINARY PROPOSAL C-l
D. ERRATA AND ADDENDA TO SCHARF, ET. AL. (1977) D-l
R. REFERENCES R-l
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I. INTRODUCTION
A recent report by Scharf, Hellman, and Bauer (1977) examined data from
23 studies in which subjects had judged the subjective magnitude of a large
variety of noises. The aim of the Scharf, et. al. (1977) investigation was
to determine how well various frequency weightings (presently incorporated
or proposed for use on sound level meters) and calculation procedures assess
the subjective magnitude of noise. One important conclusion, based on a total
of over 600 spectra, was that the calculation procedures predicted subjective
magnitude with less variability* and with greater validity** than did the
frequency weightings.
Among the six frequency weightings studied, the B- and C-weightings
were the poorest predictors of subjective magnitude while the D1-, D2-,
and E-weightings were the best predictive weighting functions. It was also
noted that the A-weighting was less than 0.5 dB more variable than the D1-,
D2-, and E-weightings. Among the five calculation procedures studied,
Stevens's Mark VI (1961), Mark VII (1972), and Zwicker's (1958) loudness
calculation procedures were the least variable, but Perceived Noise Level
(Kryter 1959) was almost as reliable. Tone-corrected Perceived Noise Level
(following the FAR 36 procedure, 1969) was a somewhat poorer predictor. Mark VI
and Perceived Noise Level yielded the calculated values that were closest, on
the average, to the observed or judged values, although all of the frequency
weightings and computational procedures examined were about equally variable
in this respect.
*The index of variability was the standard deviation of the calculated levels
of a group of sounds judged subjectively equal or the standard deviation of
differences between calculated and judged levels. These typically ranged
from 2 to 4 dB.
**The calculation procedures yielded an absolute calculated level closer to
the observed level.
1
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The objectives of the present investigation are (1) to determine
whether subjective judgments of particular types of noise, categorized
by spectral shape, are better approximated by some descriptors (frequency
weightings and calculation procedures) than by others, and (2) to investigate
the role of tonal components in these studies and to examine the relevancy
of existing tone-correction procedures.
Each of these aims is addressed separately with overall results and
conclusions provided in Section IV. Appendices A, B, and C include more
detailed analyses.
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II. SPECTRAL SHAPE
Particular types of noise often have distinctive spectral characteristics
such as the low-frequency spikes of transformer noise, the low-frequency
emphasis of vehicular noise, the mid-frequency bulge of many machine noises,
the high frequencies of an electric bell, and so forth. In the earlier report
(Scharf, et. al. , 1977, Table V), twenty of the studies examined were classi-
fied according to the specific source or type of noise. The six sources
considered were aircraft, industrial, vehicular, and household, as well as
artificial and miscellaneous noises. A statistical analysis of the differ-
ences among the data for these six noise sources was performed in the present
study. For purposes of this analysis, the vehicular noise category, for
which there was only one set of data, was combined with the aircraft noise
category to form a general transportation noise group, thus yielding a total of
five source types. As shown in Table I, a partially hierarchical analysis of
variance (ANOVA, Winer, 1962) revealed no significant differences in the
predictive ability of the ten descriptors among the five source types.
However, the interaction between source type and descriptor was significant
(p < .01). Despite the statistical significance of this interaction, the
differences among the descriptors are too small to provide a basis for
concluding that certain types of noises are better assessed in any meaningful,
practical sense by one particular descriptor than by another. Moreover, the
small number of studies contained within each source type category indicates
that noise source type and study are confounded.
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Table I
Summary Table for Partially Hierarchical ANOVA;
Five Source Types by Ten Descriptors (PNLC Has Been Omitted)
Source of Variance Sum of squares
Source type
Between groups
(error term)
Descriptor
Descriptor by source
Within groups
50
175
63
36
97
.92
.20
.05
.51
.60
Degrees of Mean
Freedom Square
4
22
9
36
198
12.73
7.96
7.00
1.01
.49
F P
1.60 NS
14.21 <.001
2.06 <.01
(error term)
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The lack of significant differences among source types may, in fact,
be attributable to the rather gross classification scheme whereby a
wide variety of spectral shapes were included within each source type.
Thus, this analysis may have obscured real differences among spectral
shapes. A more homogeneous classification can be achieved by regrouping
spectra from different studies according to spectral type or shape. It is
possible that for certain spectral shapes, particular descriptors (frequency
weightings or calculation procedures) predict subjective judgments better
than other descriptors. If so, descriptors could then each be applied, in prac-
tice, to those spectral shapes to which they are best suited. Accordingly, each
noise spectrum within the 19 studies listed in Table II of Scharf, et. al.
(1977)* was placed into one of nine spectral categories: (1) negative slope,
(2) positive slope, (3) broadband and flat, (4) narrow band, (5) U-shaped,
(6) inverted U-shaped, (7) low-frequency peaks or valleys, (8) mid-to-high
frequency peaks or valleys, and (9) mixed peaks or valleys. Figures 1 to 9
provide examples of sound spectra from each of the nine main categories. The
spectra represent noises from both artificial and natural noise sources.
(Appendix A gives more detailed definitions of the spectral shapes and a more
detailed breakdown within the main spectral categories.)
Table II presents the standard deviations (SDs) averaged across the nine
spectral categories for (1) those sets of subjective data that did not provide
judged loudness levels, (2) those that did, and (3) all spectra combined.**
*The data by Pearsons, et. al. (1968) were not included in this analysis. Wells
300 and Wells 400 are counted as one study.
**The SDs for each spectral category are provided in Tables A-2 and A-7 of
Appendix A. Note that the means of the SDs were computed without regard
to the number of SDs contributed by each category.
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BERGLUND,ET AL 1976 PILEDRIVER
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Frequency (Hz)
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Figure 1. Spectral Category 1A (Strong Negative Slope)
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Figure 2. Spectral Category 2 (Positive Slope)
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Figure 3. Spectral Category 3 (Broadband Flat)
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Figure 4. Spectral Category 4 (Narrow-band Noise)
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SPIEGEL N20
THIRD OCTAVE
(64 PHONS)
10
Figure 5. Spectral Category 5 (U-Shaped)
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Figure 6. Spectral Category 6 (inverted U-shaped)
11
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1 I 1 T I I I I
Figure 7. Spectral Category 7 (Low-Frequency Peaks and Valleys)
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Figure 8. Spectral Category 8 (Mid-to-High Frequency Peaks or Valleys)
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WELLS 1970 AIRCRAFT NOISE 12 3-3-77
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Figure 9. Spectral Category 9 (Mixed Peaks or Valleys)
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Table II
Variability of Calculated Levels of Noises
Grouped by Spectral Category or by Study
(Standard deviations in decibels computed either from the calculated levels of
a group of sounds judged subjectively equal or from the differences between
calculated and judged levels (loudness levels). The smaller the standard
deviation, the closer the scheme comes to predicting the measured subjective
equality of a set of sounds.)
SOURCE N/n
Spectral categories
(Based on calculated
levels)
Spectral categories 335/56
(loudness levels only)
Spectral categories 633/90
(total)
Descriptors
Dl D2 E
VI
VII PNL ZWI
298/34 2.7 2.2 2.3 2.1
2.8 2.6
Grouped by study (total) 763/28 3.1
from Scharf, et. al.
(1977) Table II
corrected
1.9
2.1 2.2
2.7 2.6 2.2 2.3
2.7
2.7 2.7 2.6 2.3 2.2 2.6
2.7
2.9 3.0 3.0 3.0 2.4 2.4 3.1 2.3
2.5
2.4
LEGEND:
N = number of spectra
n = number of standard deviations
A = standard sound-level meter
weighting
Dl = sound-level meter weighting,
better known as D, adopted
by International Electro-
Technical Commission (1975).
D2 = sound-level meter weighting
proposed by Kryter, K.D.
(1970), Table 2.
E = sound-level meter weighting proposed
by Stevens (1972) and circulated as
ANSI Draft document Sl.XX/104
Mark VI = ANSI S 3.4 (R1972) procedure
for the computation of loudness
of noise.
Mark VII = proposed by Stevens (1972)
PNL = perceived noise level
ZWI = based on Zwicker (1958). Computer
program from Paulus and Zwicker
(1972)
15
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Table II also presents the SDs previously calculated across studies (Scharf,
et_._ al^_, 1977, Table II, with the minor corrections given in Appendix D of this
report).
As shown in Table II, most of the sounds represented in row 1 of Table
II were judged with respect to some evaluative attribute such as noisiness,
unacceptability, etc., whereas the sounds represented in row 2 were judged
only with respect to loudness. Thus, the data contained in rows 1 and 2
demonstrate the same tendency noted in Scharf, et. al. (1977, Table V). Those
data showed that the studies in which loudness was judged yielded larger SDs
than those studies in which an evaluative attribute other than loudness was
judged. The difference, however, was not statistically significant. The most
probable basis for the difference, described in detail in Appendix B, is the
wider range of levels covered by the loudness studies than by those studies in
which an evaluative, attribute was judged.
The most revealing comparison in Table II is between overall SDs calculated
across spectral categories (row 3) and those calculated across studies (row 4).
Except for the A-weighting, paired SDs do not differ between rows 3 and 4 by
more than 0.1 dB. Thus, classifying the spectra according to shape does not
reduce overall variability. Underlying this analysis was the assumption that
a descriptor would be less variable if applied to groups of spectra of the
same shape than to groups of spectra of different shapes. Although variability
is not reduced when calculated across all the spectral categories, it may be
smaller for particular descriptors applied to particular spectral categories.
The interaction between category and procedure is considered in Table III.
16
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Table III
Summary Table for Partially Hierarchical ANOVA:
Nine Spectral Categories by Ten Descriptors
Source of Variance
Sum of squares
Degrees of Mean
Freedom Square
Source type
Between groups
Descriptor
Descriptor by source
Within groups
143.18
563.91
28.64
38.70
161.04
8
71
7
56
497
17.90
7.94
4.09
.69
.22
2.25
12.63
2.13
<.05
<.001
<.001
17
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Table III presents ANOVA for spectral type or shape by descriptor.
This analysis shows that (1) the differences among the nine spectral cate-
gories were significant at the .05 level, and (2) the differences among
the ten descriptors were statistically significant at the .001 level.
Further, the interaction between spectral shape and descriptor was signifi-
cant at the .001 level. However, despite this significant interaction, a
meaningful multiple contrasts test could not be performed due to large
variations in numbers of spectra and in numbers of SDs among the nine cate-
gories .
Also relevant to the analysis by spectral categories is the question
of differences between calculated and observed loudness levels. Table
IV, based partly on Table A-10 in Appendix A and partly on Table IV in
Scharf, et. al. (1977), gives the overall means of the mean differences for
over 300 noises grouped either by spectral category or by study. The corre-
sponding SDs of the mean and total ranges are also shown. Except for Zwicker's
loudness calculation procedure and Mark VII after the required addition
of an 8-dB constant, all the descriptors are more discrepant for the sounds
grouped by spectral category than for the sounds grouped by study. Of
more importance, however, is the variability of the mean difference. Both
the range and SDs are significantly smaller (p < .01 by t-test) for the sounds
grouped by spectral category than for those grouped by study, with the sole
exception of the SD for the A-weighting. This decreased variability is
especially noteworthy since studies that differed with respect to procedures,
standards, and instructions were broken up and individual spectra assigned to
various spectral categories. These methodological differences would be
expected to increase variability. Since the opposite occurred, it is likely
18
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Table IV
Calculated Minus Observed Loudness Levels
(Mean Differences in Decibels)
(Overall means based upon differences for 335 spectra grouped according to
spectral type as per Table A-10 in Appendix A. Overall means are also shown
for the same spectra when grouped by study as per Table IV of Scharf, et
1977.)
By Spectral Category
Mean of Mean Differences -12.1
S.D. of Means
Range
By Study
Mean of Mean Differences
S.D. of Means
Range
A
-12.1
4.8
16.0
-10.8
4.5
17.8
Dl
-5.3
4.0
12.6
-4.5
4.7
18.8
D2
-5.8
4.3
13.7
-5.0
4.8
19.3
E
-6.8
4.1
12.6
-6.2
4.6
17.7
VI
-1.2
3.2
11.6
-0.1
4.5
17.4
VII
-8.6
3.2
11.1
-6.9
4.3
15.3
PNL
-1.4
3.1
10.8
-0.0
4.7
19.3
ZWI
3.1
3.0
8.8
5.1
4.2
14.7
19
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that grouping by spectral shape meaningfully enhances the validity of
the descriptors. Moreover, the four calculation procedures with their much
greater flexibility showed a larger drop in variability than did the weight-
ing functions. In contrast, the A-weighting with its strong deemphasis of low
frequencies revealed an increase in the standard deviation. As can be seen in
Table A-10, the A-weighting grossly underestimated the level of sounds with
much energy in the low frequencies and less grossly underestimated spectra
with little energy in the low frequencies. To a lesser extent, the other
frequency weightings also deemphasize low frequencies, and this deemphasis
becomes detrimental at high levels (Scharf, et. al., 1977, Figures 6 to
8).
Furthermore, it should be pointed out that categories 7, 8 and 9 which are
distinguished by the presence of low-frequency spectral peaks or valleys,
mid-to-high-frequency peaks or valleys, and mixed peaks or valleys, respec-
tively, include many sounds wJ^h tonal components. Defined as projecting at
least 3 dB above their neighboring third-octave bands (see Section III), tonal
components were identified in over 80 percent of the sounds in categories
7 and 8, and in 30 percent of those in category 9. The SDs are presented in
Tables A-12 and A-13 of Appendix A. No clearcut differences were found between
those spectra with tones and those without (except for part of category 9, as
discussed in Appendix A). The general problem of tonal components is treated
next, in Section III.
20
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III. TONAL COMPONENTS
A number of studies have reported that people react more negatively
to noises containing tonal components than to the same or similar noises
without tonal components. Tonal components appear to add more to the unpleasant-
ness of a noise than the same amount of acoustical energy would add if
spread over a wide band of frequencies. Reports in the literature (Copeland,
1960; Hargest and Pinker, 1967; Kryter and Pearsons, 1965; Little, 1961;
Little and Mabry, 1969; Pearsons, 1968; Pearsons and Bennett, 1969, 1971;
Pearsons, Bishop and Horonjeff, 1969; Pearsons and Wells, 1968, 1969;
Wells, 1967, 1969b) show that tonal components add the equivalent of from 2
to 15 dB or more to the annoyance of a sound than would be expected from the
increase in overall energy. Several reports show that loudness or noisiness,
as distinct from annoyance or objectionability, is not affected by the
presence of tonal components (Fishken, 1971; Kryter and Pearsons, 1963;
Rule, 1964; Rule and Little, 1963). One report (Niese, 1965) showed that
tonal components affected both loudness and annoyance to the same degree.
Another report (Goulet and Northwood, 1972) found no effect of tonal compon-
ents on either loudness or annoyance. In both these studies stimuli were
presented at levels between 45 and 75 dB sound pressure level. On the other
hand, the investigations showing that tonal components do contribute unduly
to annoyance were conducted mostly at levels of 85 dB and higher.
The present report evaluates a number of the studies cited above. Some
studied sounds with tonal components artificially added (Fishken, 1971;
Pearsons and Wells, 1969; Wells, 1969b), and others studied natural sounds
that contained tonal components (Pearsons and Bennett, 1969, 1971; Wells,
21
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1970, 1972). Although many studies not cited above, but examined in Scharf,
et. al. (1977), did include some noises with tonal components, such noises
did not usually constitute a large part of a given study. Nevertheless, to
provide a preliminary analysis of the effect of pure tones on judgments of
loudness and annoyance, 27 of the 28 sets of SDs from Scharf, et. al. (1977)
were divided into two groups.* One group of 12 SDs was obtained from subjective
judgments of spectra without tonal components, and a second group of 15 SDs
was obtained from subjective judgments produced by spectra that contained
tonal components. The presence of tonal components was based on the respective
authors' definitions. The results are found in Scharf, et. al. (1977),
Table V.
A partially hierarchical ANOVA (Lynch and Huntsberger, 1976) based on
those data revealed no significant difference between the SDs for 10 of the
11 descriptors (PNL tone corrected in accordance with FAR 36 was omitted).
The interaction between the presence or absence of tonal components and
descriptors was also not significant. This negative finding, however, may
not be meaningful. First, many of the studies included within the group
without tonal components had a few spectra with components. Second, other
differences (such as attribute judged) among studies could have obscured
any effects of tonal components on the variability of the descriptors.
Tiird, and most important, is that if the effect of tonal components is to
increase the unpleasantness of a sound, then sounds all or most of which
contained tonal components would all be more or less equally affected. Most
of the descriptors would then show no change in their variability unless
"absolute" levels were measured. Such levels were not measured in most of
*The data by Robinson and Bowsher (1961) were not included in this analysis,
22
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the studies involving sounds with tonal components; sounds were usually all judged
equal to a standard, and hence only a measure variability was meaningful.
For the present report, a detailed analysis of more than 600 spectra*
from Scharf, et. al., (1977) was undertaken to identify those spectra that
contained tonal components. The criterion for identification of a tonal
component was that a third-octave band must have a level at least 4.75
dB above that of either of the immediately adjacent third-octave bands.
This criterion was adopted to assure that the tone is at least 3 dB above
the noise in the band of interest, and is similar to the FAR 36 procedure.**
If the 4.75 dB criterion is exceeded, then the tone in the given third-octave
band must be at least 3 dB above the level of the noise in the band that
contains it. It was felt that, rather than rely on the authors' definition
of tones which may vary among authors, a precise identification of the
spectra containing tonal components would permit a finer determination
of how well the different sound descriptors handle such stimuli. (A partial
analysis of this type is presented in Appendix B for individual studies.)
Several procedures specifically designed to "correct" for tonal compo-
nents will be evaluated in addition to the eight descriptors examined in
Section II. These include the FAR 36 (1969) procedure, which was identified
as PNLC in Scharf, et. al. (1977); a different correction to Perceived Noise
Level proposed by Kryter and Pearsons (1965); and a procedure tentatively
proposed by S. S. Stevens (1970) explicitly for use with Mark VII but appli-
cable to any of the other descriptors. To augment the power of these analyses,
a large-scale study by Ollerhead (1971, 1973) has been added to the
*The data by Pearsons, et. al. (1968) were not included in this analysis.
**No distinction is made between a "true" tonal component and a sharp
increase in level over a restricted range of frequencies.
23
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original group of studies examined in Scharf, et. al. (1977). Not only do
these additional 104 spectra include many stimuli with tonal components, but a
iudged level for each of the stimuli is provided as well.
1. Composition of Studies with Respect to Tonal Components
More than 500 spectra with and without tonal components including 104
spectra from Ollerhead (1971, 1973) underlie the analysis described in
this section. Of approximately 300 spectra with tonal components, over
one fourth contained more than one tone. Most single components fell between
500 and 2000 Hz; the remainder were nearly evenly divided between those at
frequencies below 500 Hz and those above 2000 Hz. With respect to tone-to-
noise ratio, over half the components were less than 13 dB above the surroun-
ding third-octave bands, one third were between 14 and 23 dB, and less than
one tenth were more than 23 dB above the noise. Approximately half the tonal
components were at a sound pressure level between 60 and 80 dB, 30 percent
were above 80 dB, and 20 percent at 60 dB or lower.
2. Evidence Demonstrating a Need for a Tone Correction
As noted above, tonal components may contribute unduly to the unpleasant-
ness of noise. If so, then those groups of noises that are a mixture of
sounds both with and without tonal components ought to show more variability
for a given descriptor than either a group of noises all with tonal compon-
ents or a group of noises all without. Accordingly, the whole set of noises
was first examined for this posited difference in variability without regard
to the attribute judged (whether loudness or some evaluative attribute),
24
-------
tone-to-noise ratio, or overall level, parameters which may in fact be
relevant to the effect of tonal components on human response.
Table V presents the standard deviations for 542 spectra from 13 studies
and subsets listed in column 1, Table VI, that had at least three spectra
with tonal components and at least three without. The mean SDs for all the
sets of spectra, both with and without tonal components, are given in the
first row, followed by the mean SDs for those spectra with tonal components,
and then by those without tonal components. The SD of the SDs upon which
the mean values are based are also shown. For every descriptor the SD for
the overall group is larger than the SD for either subgroup. This result
suggests that sounds with tonal components are judged somewhat differently
from sounds without; that effect is apparent for this analysis even when
studies that contained relatively soft sounds judged with respect to loudness
are included.
However, when just those studies are examined that involved evaluative
judgments of annoyance, unacceptability, etc. (and studies that involved
loudness judgments are excluded), the picture is altered. Table VII shows
that in the annoyance studies, those spectra with tonal components produced
the largest SDs under all eight descriptors, while those spectra without
tonal components produced the smallest SDs. The presence of tonal components
made the descriptors more variable without apparently affecting the SDs
obtained for the mixture of sounds both with and without tonal components.
Had spectra with tonal components been judged differently, on the average,
than spectra without tonal components, the SDs for the overall group would
have been increased, not decreased slightly as they are in Table VII.
25
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Table V
Standard Deviations (In Decibels) for Spectra Both
with and without Tonal Components, for Spectra with
Tonal Components, and for Spectra without Tonal
Components. (Means were Unweighted. Attribute Judged:
Loudness, Annoyance, Noisiness, Etc.)
Number
of Number* Frequency Weighting Calculation Procedure
Spectra of SDs A Dl D2 E VI VII PNL ZWI
Mean SD (in decibels)
Spectra Both
with and without
components 542
Spectra with
tonal components 314
Spectra without
tonal components 205
29 3.1 3.0 3.1 2.9 2.6 2.7 2.8 2.7
29 2.6 2.4 2.4 2.3 2.1 2.1 2.4 2.3
20 2.7 2.4 2.6 2.3 2.1 2.1 2.2 2.4
SD of SDs (in decibels)
Spectra Both
with and without
tonal components
Spectra with
tonal components
Spectra without
tonal components
1.2 1.2 1.2 1.2 1.1 1.4 1.0 1.2
1.4 1.2 1.3 1.2 , 1.0 1.1 1.2 1.4
1.6 1.3 1.4 1.4 1.4 1.5 1.3 1.5
*The number of SDs varies because some studies do not contain at least 3 spectra
required for the computation of a standard deviation.
26
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Table VI
Studies that Contributed Spectra to the Analysis in Table V
Studies that Contributed to Both
the 542 and 314 Spectra
Study
Borsky
Fishken
Jahn
Ollerhead
Pearson
Pearson
Spiegel
Wells
Wells 3
Wells (
Wells (
Yaniv
Studies that Contributed to
205 Spectra
et. al.
id
i and Bennett
; and Wells
10-400 Series
inpublished)
FHV)
Year
1974
1971
1965/66
1964
1971, 1973
1969
1969
1960
1970
1969a
c. 1970
1972
1976
Study
Jahn
L'ubcke, et . al .
Ollerhead
Pearsons and Bennett
Pearsons and Wells
Spiegel
Wells
Wells 300-400 Series
Wells (Unpublished)
Yaniv
Year
1965/66
1964
1971, 1973
1969
1969
1960
1970
1969a
c. 1970
1976
27
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Table VII
Standard Deviations (In Decibels) from Studies Involving
Mainly Judgments of Annoyance or Unacceptability, for
Spectra Both with and without Tonal Components, for
Spectra with Tonal Components, and for Spectra without
Tonal Components. (Means were Unweighted.)
Number
of
Spectra
Number Frequency Weighting Calculation Procedure
of SDs A Dl D2 E VI VII PNL ZWI
Mean SD (in decibels)
Spectra with
and without
components
260 13 2.5 2.0 2.1 1.9 1.9 1.9 2.1 2.8
Spectra with
tonal components
Spectra without
tonal components
150 12 2.8 2.2 2.2 2.1 2.1 2.1 2.4 2.9
106 11 1.9 1.6 1.8 1.4 1.2 1.3 1.4 2.3
SD of SDs (in decibels)
Spectra with
and without
tonal components
Spectra with
tonal components
Spectra without
tonal components
1.2 0.8 0.9 0.8 0.8 0.9 0.9 1.5
1.5 1.1 1.3 1.1 1.0 1.1 1.2 1.6
1.2 0.8 0.9 0.9 0.7 0.7 0.7 1.8
Studies that Contributed to Both
the 260 and 150 Spectra
Study Year
Borsky
Pearsons and Bennett
Pearsons and Wells
Wells
Wells 300-400
Wells (Unpublished)
1974
1969
1969
1970
1969a
1970
Studies that Contributed to
106 Spectra
Study Year
Pearsons and Bennett
Pearsons and Wells
Wells 300-400
Wells (Unpublished)
1969
1969
1969a
1970
28
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Perhaps combining results from diverse studies that used widely different
methods and instructions obscures the possible effect of tonal components on
judged annoyance. Moreover, any interpretation of these findings must be
limited due to the absence of measurements of "absolute" judged levels of
annoyance.
The relevance of the attribute judged is further shown by breaking
Table V's 314 spectra with tonal components into two groups, those for
studies in which annoyance and noisiness were judged, and those in which
loudness was judged. Table VIII shows that five of the eight descriptors are
more variable for the annoyance and noisiness judgments than for the loudness
judgments; the other three are about the same for both attributes. However,
the mean SD for annoyance across the eight descriptors' is 2.5 dB compared to
2.2 dB for loudness. Such a small difference, 0.3 dB, is not meaningful.
Earlier studies suggested that tonal components would be a significant
factor at high sound pressure levels — in annoyance judgments — but not
at moderate or low levels. If so, a group of sounds with tonal components
judged with respect to annoyance should yield more variable descriptors when
a mixture of both low and high level sounds are included than when only low
or only high levels are included. Of the 233 spectra with tonal components
in Table VIII that were judged for annoyance and noisiness, 121 were at or
above an overall sound pressure level of 80 dB. Table IX shows that the SDs
for the 233 spectra are, on the average, larger by 0.1 dB than the SDs for
the 121 high level sounds. This difference is too small to be meaningful.
29
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Table VIII
Mean Standard Deviations (In Decibels) for Spectra with
Tonal Components Based on Annoyance, Noisiness, and Loudness Judgments
Number
Attribute of No. of Studies/ Frequency Weighting Calculation Procedure
Judged Spectra No. of SDs A Dl D2 E VI VII PNL ZWI
Annoyance 233 8/17 2.9 2.4 2.4 2.3 2.2 2.3 2.5 2.7
and Noisiness
Loudness 81 5/12 2.2 2.5 2.5 2.3 2.0 1.9 2.3 1.6
30
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Table IX
Standard Deviations in Decibels for 233 Spectra with
Tonal Components at Moderate and High Sound Pressure
Levels Compared to Standard Deviations in Decibels for
121 Spectra at or above an Overall Sound Pressure Level
of 80 dB.
Number
of No. of Studies/ Frequency Weighting Calculation Procedure
Spectra No. of SDs A Dl D2 E VI VII PNL ZWI
233 8/17 2.9 2.4 2.4 2.3 2.2 2.3 2.5 2.7
121 4/11 3.2 2.3 2.5 2.3 2.1 2.1 2.2 2.1
31
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Closely allied to overall level of the tone is the tone-to-noise ratio.
Only Mark VII and Perceived Noise Level were compared for two ranges of
tone-to-noise ratios. Over the range of 3 to 13 dB (relative to the third-
t
octave band level), the mean SD was around 1.6 dB; over the range of 14 to 23
dB, the mean SD increased to around 2.7 dB. Thus, based on the data examined
in this report, both Mark VII and Perceived Noise Level, and presumably the
other descriptors, may be less accurate in assessing human response to sound
when the tone projects out well above the noise i.e., none of the descriptors
may adequately assess the subjective annoyance produced by relatively strong
tones.
The effect of the frequency of the tonal components could not be ade-
quately evaluated since in the annoyance studies most of the tones were
between 500 and 2000 Hz. For 19 spectra with tonal components below 500 Hz,
the mean SD was 0.9 dB for Mark VII and 1.5 dB for Perceived Noise Level.
For 22 spectra with tonal components above 2000 Hz, the SDs increased to 2.9
dB for Mark VII and to 2.4 dB for Perceived Noise Level. Given the small
sample sizes, this finding is highly tentative although it is consistent with
the analysis of anomalous studies in Appendix B.
The role of the number of tonal components was also ascertained.
Several of the Wells (1969a, 1970, 1972) studies and the Ollerhead (1971,
1973) study contained sounds with multiple tones as well as with single
tones. The SDs for Mark VII and Perceived Noise Level were not unusually high
for the group of spectra with both single and multiple tones. In the
Ollerhead study, as seen in Table X, the SDs produced by the mixture of
single and multiple tones is only slightly larger (0.3 dB) than the SDs
produced by spectra with multiple tones only. These preliminary findings
suggest that the number of components may not affect the variability of the
descriptors.
32
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Table X
Analysis of Standard Deviations in Decibels for Mark VII and Per-
ceived Noise Level Produced by Data from Ollerhead (1971) Based on
Spectra that Contained Both Single and Multiple Tones and Spectra
with Multiple Tones Only.
Number of
Spectra Mark VII PNL
Mean SD (in decibels)
Spectra with Single and
Multiple Tones 60 3.2 3.1
Spectra with Multiple
Tones Only 33 2.9 2.8
33
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The preceding analysis of the effect of tonal components on the variability
of the descriptors obviously does not lead to clear-cut conclusions. However,
the main effect of tonal components on human response appears, from earlier
studies, to be an increase in the aversiveness of broadband sounds. Thus, it
is essential to examine the mean differences between calculated and observed
levels. Only Ollerhead (1971, 1973) provided observed levels based on judgments
of an evaluative attribute — noisiness; the remaining observed levels are
based on loudness. Table XI shows the mean differences from a common group of
studies listed in Table XII that had some sounds with tonal components and some
sounds without. The differences are just about the same for the two sets of
spectra; adding tonal components appears to have little effect on the dis-
crepancy between calculated and observed levels. Since none of the eight
descriptors makes special provision for tonal components (except, as an integral
part of the Zwicker procedure), the lack of any effect of tonal components on
the mean differences suggests that adding tones does not increase the subjective
magnitude. Moreover, the variability of the mean difference is greater for
spectra without tones than for spectra with tones. Taken together, the overall
results in Table XI imply that a tone correction procedure may not be needed
when the judged attribute is loudness.
The effect of tonal components is different, however, for those sounds that
were judged with respect to noisiness in the Ollerhead (1971, 1973) study. Those
mean differences, listed separately in Table XI, are more positive for the 44
spectra without tonal components than for the 60 spectra with tonal components.
This suggests that the observed levels were higher for the spectra with tones
than for those without. The increase in the mean difference is 1.8 dB, averaged
34
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Table XI
Mean Differences in Decibels (Calculated Minus Observed Levels)
for Studies Containing Some Sounds with Tonal Components and
Some without. (Attribute Judged was Loudness Except in the
Ollerhead (1971, 1973) Study which is also Listed Separately.)
Frequency Weighting Calculation Procedure
Number of
Spectra A Dl D2 E VI VII PNL ZWI
Mean of Mean
Differences
Spectra without
tonal components 99 -7.9 -2.0 -2.6 -3.5 3.0 -4.0 4.0 7.5
Spectra with
tonal components 141 -7.7 -1.0 -1.5 -2.9 2.9 -4.6 4.1 7.1
SD of SDs
Spectra without
tonal components 5.6 5.7 5.4 6.1 5.8 6.2 6.6 5.3
Spectra with
tonal components 4.7 4.9 5.0 4.6 4.0 4.0 4.8 3.3
Ollerhead only
(Noisiness judged)
Mean Differences
Spectra without
tonal components 44 -3.1 2.7 1.9 1.5 7.2 1.0 9.9 11.9
Spectra with
tonal components 60 -5.3 1.0 -0.1 -0.1 5.8 -1.3 7.9 10.2
35
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Table XII
Studies that Contributed Spectra to The Analysis in Table XI
Studies that Contributed to
141 Spectra
Study Year
Fishken 1971
John 1965/66
Lubcke, et. al. 1964
Ollerhead 1971
Spiegel 1960
Yaniv 1976
Studies that Contributed to
99 Spectra
Study Year
John
L'ubcke. et. al.
Ollerhead
Spiegel
Yaniv
1965/66
1964
1971
1960
1976
36
-------
over the eight descriptors. The most likely interpretation of this result
is that in the Ollerhead (1971, 1973) study, aircraft sounds with tonal
components were judged the equivalent of 1.8 dB noisier than sounds without
tonal components. Further, it should be noted here that, in contrast to the
other studies listed in Table XII, the noise stimuli in the Ollerhead (1971,
1973) study had an overall sound pressure level greater than 80 dB.
In general, the studies examined in this report provide little evidence
for the need for a tone correction. This finding only appears to contradict
conclusions drawn from some studies cited above. However, the reasons for the
apparent disagreement may be found in the specific nature of the studies
examined in the present report. (See Section IV below.) Furthermore,
Ollerhead's (1971, 1973) data on the aversiveness of sounds with tonal compo-
nents at high levels do suggest a need for a tone correction, but only of the
order of 2 dB. Despite this generally negative result, the following section
examines and evaluates several tone-correction procedures.
3. Descriptions of Tone-Correction Procedures
a) PNLC or FAR 36 Tone Corrections
A tone correction is contained within the FAR 36 (1969) aircraft certi-
fication regulation. The tone correction was included to increase, in
accordance with subjective judgments, the measured Perceived Noise Level of
aircraft that produced noise spectra with tonal components. The Perceived
Noise Level is calculated in the usual way for a given spectrum (Kryter,
1959) - The FAR 36 procedure then smoothes the spectrum and compares the
original spectrum to the smoothed spectrum in each third-octave band. If a
band level of the original spectrum exceeds the corresponding band level of
the smoothed spectrum by 3 dB or more, then a correction in decibels is
37
-------
added to the calculated Perceived Noise Level to account for the presence of
discrete tones. Thus, within the FAR 36 procedure, the criterion for a tonal
component is that it exceed the noise level in the third-octave band contain-
ing it by 3 dB or more. The number of decibels added to the calculated
Perceived Noise Level depends on the frequency of the tone and its level
relative to the smoothed third-octave band noise level. Tones between 500
and 5000 Hz are penalized twice as much (in decibels) as tones below and
above that frequency range. The correction cannot exceed 6.67 dB, which is
the penalty for a tone 20 dB or more above the noise level. Between tone-to-
noise ratios of 3 dB and 20 dB, the penalty increases linearly with level,
more rapidly in the middle frequency range than elsewhere. If more than a
single tonal component is identified, only the largest penalty is added to
Perceived Noise Level; in essence, multiple tonal components are ignored and
a correction is applied only to the strongest tone (taking into account
frequency and tone-to-noise ratio). This procedure does not take absolute
level into account, presumably because it was designed explicitly for high-
level aircraft noise. Figure 10 illustrates how the FAR 36 procedure
depends on tone-to-noise ratio and on the frequency of the tone.
b) Kryter and Pearsons's (1965) Tone-Correction Procedure
Like the FAR 36 method, the procedure proposed by Kryter and Pearsons
(1965) is designed for use with Perceived Noise Level. It is henceforth
referred to in this report as PNLKP. Instead of first calculating Perceived
Noise Level and then adding a correction in decibels as in the FAR 36 method
PNLKP first corrects the levels of each third-octave band containing identi-
fied pure tones, and then calculates Perceived Noise Level according to
38
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I I I I I I I I I I I I -j[—r |j | |
O
c
o
S
t
o
O
o
I I
500 5000 HZ
I I i
I I I I
10 15
Level Difference F,dB
20
25
Figure 10. FAR 36 Procedure Tone-Corrections
39
-------
Kryter (1959) on the basis of the revised spectrum. The result is a tone-
corrected Perceived Noise Level. In the current application a correc-
tion is made for each band identified as containing a pure tone at third-
octave band center frequencies. Only tones 3 dB or more above adjacent
third-octave bands have been identified as pure tones in this report although
Kryter and Pearsons (1965) suggested a correction for even smaller tone-to-
noise ratios. Figure 11 shows that the value of the correction within each
band increases with increasing tone-to-noise ratio up to a maximum ratio of
25 dB. The value also varies continuously with frequency with a flat maximum
between 3000 and 4000 Hz, depending on tone-to-noise ratio.
c) Stevens's (1970) Preliminary Tone-Correction Procedure
In 1970, S. S. Stevens circulated a tentative proposal for a tone-correc-
tion method to be used with his Mark VII or Mark VI computational procedures.
His correction was based on the notion that the underestimation of the calcu-
lated perceived magnitude of a tone-and-noise complex according to Mark VI
or VII arises because the auditory system analyzes components in the complex
as distinct sounds and then, in effect, adds them together to obtain a
total percept. To develop a procedure that would mimic the auditory system,
Stevens turned to data on the masking of a pure tone by broad-band noise. He
assumed that the loudness of the partially masked tone would summate with the
loudness of the noise when the two are judged as a composite sound. Stevens's
procedure takes into account the fact that partial masking depends on the
tone-to-noise ratio as well as on the absolute level of the noise.
40
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•§ 5
•O Q.
3-s
A. Octave T/N
band T-N/AN
B. 1/3 octave T/N
band T-N/AN
C. 1/10 octave T/N
band T-N/AN
25dB
25dB
25dB
25dB
Figure 11. Decibel Correction to be Added to Sound Pressure
Level of a Band Containing Pure-Tone Component Prior
to Calculation of Perceived-Noise Level. Parameter
is Band Center Frequency. Abscissa is Either Ratio,
in decibels, Between Tone and Noise Measured Sepa-
rately within a Band (T/N) or the Ratio Between Level
of Band with Tone and Noise Together and Level
of Adjacent Bands (T+N/AN) when Measured with
Full-, 1/3-, or 1/10-Oct-Band Filters (from Kryter
and Pearsons, 1965).
41
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Stevens did not state what criterion to use for identifying the presence
of a tonal component. Thus, the same 3-dB criterion described above for
PNLC was applied to Stevens' correction procedure. Once identified, the
tonal component was removed from the spectrum by averaging the levels of the
immediately surrounding third-octave bands. The Perceived Level is then
calculated by means of Mark VII for the toneless noise spectrum. The decibel
value of the tonal component is read from curves, as shown in Figure 12.
Although Mark VII was used in constructing the curves that provided the value
of the tonal correction, Stevens' correction can be applied to any one of
the descriptors dealt with in the present report. Once the tonal component
has been removed, the particular frequency weighting or calculation procedure
is used to compute the predicted level of the toneless spectrum. Stevens'
tone-correction value in decibels is then added to that computed level.
The Stevens correction procedure differs from the FAR 36 and Kryter
and Pearsons (1965) procedures in two main respects. First, it includes the
level of the band containing the tone as an important determinant of the
value of the tone correction, and second, it omits any dependence of the
correction on the frequency of the tonal component. The Stevens procedure
also differs in that it is derived from basic psychoacoustic considerations
about the interaction between tone and noise and in that it includes an
explicit method for handling multiple tonal components.
The correction for multiple tones assumes that the tones may partly
mask or inhibit one another, the more so the closer they are in frequency.*
^Unless the tones are in the same critical band, in which case they are
treated like a single tonal component. Since a critical band is about as
wide as a third-octave band, it would require an analysis finer than the
usual third-octave band analysis to identify such closely spaced tones.
42
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A)
dB
10
9
8
0)
§ -1
i 65
\ 4
3
2
1
0
Tone addition
Noise level
in 1/3 octave
5 10 15 20
Level of tone re 1 /3 octave band
dB
B)
db
9
T
~T
C)
20
Level of tone
re 1/3 octave
band
20 30 40 50 60 70 80 90 100 dB
Noise level in 1/3 octave
db
20
18
OJ
B 16
o
o
2 14
CD
i_
£ 12
o
•t-'
- 10
QJ
>
QJ
J 8
20 30 40 50 60 70 80 90 100db
Noise level in 1/3 octave
Figure 12. (A) Curves for tone addition showing the number of decibels
(ordinate) added by the tone to the perceived level of the
broadband noise calculated without tone. The abscissa shows
the number of decibels by which the tone projects above the
1/3 octave level of th noise. The 1/3 octave level is found
by averaging the band levels above and below the band that
contains the tone. For tone projections greater tha 20 dB
the tone addition grows linearly with a slope of 1.0 (dashed
lines). (B) Same as (A), but with the parameter being the
level of the tone as it projects above the level of the
noise in the 1/3 octave band. (C) Another alternative
to (A). Here the parameter is the number of decibels to
be added to the calculated level of the noise for the tone
projections given by the ordinate (From Stevens, unpublished,
1970.)
43
-------
Mark VII is used in conjunction with the mel scale of pitch to compute the
amount of inhibition from lower to higher frequencies. Within each band,
the calculated inhibition, expresses in sones, is subtracted from the
perceived magnitude of a given tonal component, as determined by Mark VII.
This value is then converted to Perceived Level in decibels which is used in
calculating the correction to be applied for that component. Finally, the
corrections computed for each component, after inhibition is taken into
account, are all added to the Perceived Level of the toneless noise. As
with single tones, this procedure can be applied to any of the descriptors
examined in the present report. Accordingly, the Stevens procedure will be
applied to eight descriptors, with special attention to Mark VII for which
it was primarily intended.
It must be emphasized that Stevens did not publish this tone-correction
procedure, developed in 1969 and 1970, and in all likelihood intended to
modify it before publication. Therefore, it is to be considered a tentative
model that may yield insights into just how and when to apply a tone correction.
4. Other Tone-Correction Procedures
A tone-correction procedure not evaluated in this report was proposed by
Wells (1969b) for use with his general annoyance-level (ANL) procedure
for assessing negative effects of noise. This report does not deal with
his procedure primarily because it has not been as widely discussed in the
literature as other descriptors have.
44
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Zwicker's (1958) procedure may be considered a tone-correction procedure
in that it is designed to handle pure tones and combinations of tones and
noise, with respect to loudness. Only in so far as noisiness or aversiveness
differs from loudness, would his procedure require a tone correction. Tables
V and VII do not contradict such a possibility; Table VIII lends some support
since, applied to spectra with tonal components, Zwicker's procedure was the
most variable (procedure) when annoyance or noisiness was judged, and was the
least variable when loudness was judged. Zwicker's procedure handles tones
on the same basic principles of mutual inhibition that inspired Stevens's
correction procedure.
5. Evaluation of Tone-Correction Procedures
Similar to the analysis by spectral shape in Section II, evaluation
of the relative effectiveness of the three tone-correction procedures describ-
ed above consists of two parts. First, the effect of the procedures on
the variability of predicting subjective magnitude is assessed. Next, their
effect on differences between calculated and judged levels is examined.
a) Variability
Table XIII shows the SDs for 260 spectra, some with and some without
tonal components, from six studies and subsets listed in column 1, Table VII,
in which listeners judged an evaluative attribute (e.g., annoyance, unaccept-
ability). According to Table XIII, the mean SD for Mark VII corrected by
Stevens's preliminary tone-correction procedure is larger than for Mark VII
uncorrected. The outcome appears the same when the Stevens correction is
applied to the other seven descriptors, as shown in Appendix C. Similarly,
the FAR 36 (PNLC) and Kryter and Pearsons (1965) tone-correction procedures
45
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Table XIII. Effect on Standard Deviations of Three
Tone-Correction Procedures. (SDs are
given for Mark VII with and without the
preliminary tone-correction procedure of
S.S. Stevens. SDs are also given for
PNL with and without the FAR 36 correction,
listed under PNLC, and the proposed
correction by Kryter and Pearsons, listed
under PNLKP. Tonal components were present
in all the spectra or only in some.)
Attribute Number Tonal
Judged of Spectra Components
Calculation Procedures
Mark VII
Uncorrected Corrected PNL PNLC PNLKP
1.9
Evaluative Present Mean
SD (dB)
260 in
SD of
only some SDs (dB) 0.9
2.2 2.1 2.2 3.2
1.1 0.9 0.9 1.3
Evaluative
and 314
Loudness
Present Mean
SD (dB) 2.1
in
SD of
all SDs (dB) 1.1
3.0 2.4 2.6 3.5
1.4 1.2 1.2 1.8
46
-------
inflate the SDs. Thus it appears that the tone corrections do not improve
the descriptors' predictability of the negative reactions to noises that
contain tonal components. If the correction procedures had worked, differ-
ences between noises with tonal components and those without should be reduced,
and the SD of a mix of both kinds of noise should become smaller after
correcting for the presence of tones. The failure of the three correction
procedures to decrease the SDs may be due to the inclusion of many noises
below 80 dB (although none below 70 dB) where tonal components may be subjec-
tively less important than at high levels. Such a level effect would be
especially detrimental for Stevens's correction procedure which adds larger
corrections at low than at high noise levels. Nevertheless, in a separate
analysis, Ollerhead's (1971, 1973) 104 aircraft noises judged for noisiness
were almost all above 90 dB sound pressure level, and yet variability for
those noises also increased from about 3.9 dB to about 4.4 dB when either
Stevens's correction was applied to Mark VII, or the FAR 36 (PNLC) procedure
was applied to Perceived Noise Level.
Table XIII also shows that the correction procedures increase the vari-
ability for 314 spectra from 13 studies and subsets listed in column 1, Table VI,
all of which contained tonal components. In some studies, an evaluative attri-
bute was judged, in others loudness was judged. Mixing the two types of
judgments together may be part of the reason for the increase in variability
when a correction procedure is introduced. Further, the tone-correction
procedures did not decrease the variability when applied only to tone-noise
47
-------
complexes (a) with multiple tones, (b) with tones at high tone-to-noise
ratios (14 to 23 dB), (c) with tones at lower ratios (3 to 13 dB), (d) at or
above an overall sound pressure level of 80 dB, or (e) with tones below 500 Hz,
or above 2000 Hz. These results are indicated in Table XIV.
b) Mean Differences Between Calculated and Observed Levels
If the tone-correction procedures do not reduce variability of the
descriptors, do they at least reduce the discrepancy between calculated and
judged levels? Table XV shows the mean differences between calculated and
observed levels for 141 spectra with identified tonal components, from six
studies and subsets listed in column 1, Table XII. Observed levels were
calculated according to Mar-k VII, with and without a tone correction, and
according to the Perceived Noise Level (PNL), FAR 36 (PNLC), and Kryter and
Pearsons (1965, PNLKP) procedures. If the required 8-dB constant is added to
the Mark VII values to make them 3.4 and 6.7 dB, respectively, then all three
tone-correction procedures increase the over-estimation of the measured
level. More important, the corrections also increase the SDs of the mean
differences, thus indicating that calculated values vary more around their
means when corrected than when uncorrected. These 141 spectra included 81
for which loudness judgments were made and for which a tone-correction
procedure may not be needed (see Table XI). A separate analysis was also
made in Table XI of the other 60 spectra, all from Ollerhead (1971, 1973).
Those data did suggest that a tone correction of about 2 dB may be necessary
for judged noisiness.
48
-------
Table XIV. Effect of Multiple Tones, Tone-to-Noise Ratio, Sound Pressure
Level of Tone-Noise Complexes Above 80 dB, and Tone Frequency
on Mean Standard Deviations in Decibels Produced by Three Tone-
Correction Procedures.
Calculation Procedures
Parameter Number of Mark VII
Assessed Spectra Uncorrected Corrected
Evaluation of
Multiple Tones 62 2.7 2.9
Effect of Tone-to-
Noise Ratio
3-13 dB 47 1.6 2.2
14-23 d3 68 2.7 3.5
Effect of Overall
Sound Pressure
Level at or
above 80 dB 121 2.1 2.7
PNL PNLC PNLKP
2.8 3.0 3.4
1.7 1.9 1.6
2.8 2.8 3.0
2.2 2.3 2.7
Effect of Tone
Frequency (Hz)
Tones at or
below 500 Hz
19
0.9
1.4
1.5
1.5
1.7
Tones at or
above 2000 Hz
22
2.9
3.5
2.4
2.4
3.1
-------
Table XV. Mean Differences (in Decibels) (Calculated Minus Observed
Levels for 141 Spectra with Tonal Components. Attributes
Judged: Loudness and Noisiness.)
Mark VII PNL PNLC PNLKP
uncorrected corrected
Means (dB) -4.6 -1.3 4.1 7.8 7.8
SD of Means (dB) 4.0 6.9 4.8 5.8 6.7
50
-------
The results in Tables XIII, XIV, and XV do not necessarily mean that
the three proposed tone-correction procedures are basically inadequate.
Most of the data used for an assessment of the descriptors, particularly
those used for Table XIV, are based on subjective judgments produced by
spectra from either Wells (1969a, 1970, 1972) or Ollerhead (1971, 1973).
As pointed out in part 2 of this section, as well as in Appendix A, the
inconclusive findings with respect to the need for a tone-correction are most
likely due to the dearth of relevant data. Before the tone-correction
procedures can be properly assessed, a need for a correction must be clearly
demonstrated.
Ollerhead's (1971, 1973) study was the only one to provide differences
in level (relative to a specified standard) for a large group of noises
for which an aversive quality, and not loudness, had been judged. The
variability of the differences between calculated and observed levels, like
the combined results in Table XV, did not decrease for Ollerhead's (1971,
1973) noises when the three tone-correction procedures were applied. The
absolute discrepancies did go down for Mark VII (and also Mark VI) corrected
by the Stevens-correction procedure, but by less than 1 dB, from an average
overestimation of nearly 7 dB to around 6 dB. A reduction in the overestima-
tion was unexpected since the correction procedure was designed to increase
the calculated values. Stevens's procedure, however, often results in a
decrease in the calculated level, especially when the tonal components are at
low levels relative to a high-level noise as was the case with Ollerhead's
(1971, 1973) sounds. On the other hand, PNLC and PNLKP overcorrected and
increased the discrepancy between calculated and measured levels.
51
-------
6. Summary of Findings Relative to Tonal Components
The examination of large numbers of spectra with and without tonal
components lends only tentative support to the trends noted in the literature.
When the judged attribute is either loudness or noisiness, tonal components
did not seem to add to the subjective magnitude of broad-band noise for
stimuli below 80 dB sound pressure level. Only when the noise was at a high
level (above about 80 dB overall sound pressure level), did the introduction
of tonal components appear to add to the aversiveness of the noise. Above 80
dB sound pressure level, the increase in noisiness ascribed to the presence of
tonal components is about 2 dB. No data seem to be available to adequately
assess the contribution of tonal components to the "absolute" magnitude of
judged annoyance or unacceptability.
Procedures in use or proposed to correct for the presence of tonal
components did not decrease the variability of Mark VII and Perceived Noise
Level to which they were applied. The corrections also did not bring the
calculated levels closer to the measured levels. Although a small correction
may be necessary for the presence of tonal components at high levels, the
procedures now available cannot be properly assessed until more data demons-
trating the need for a tone correction become available.
52
-------
IV. CONCLUSIONS AND RECOMMENDATIONS
The present report is a continuation of an earlier report by Scharf, et.
al• (1977). The present survey sought (1) to discover whether particular
noise descriptors (sound-level frequency weightings and various calculation
procedures) are more appropriate for certain types of spectral shapes than for
others, and (2) to determine just how important tonal components are in human
response to noise and how best to take tonal components into account.
The analysis of data by spectral shape provided a mixed outcome. Results
revealed little change in the standard deviations (SDs) of eight descriptors
(frequency weightings A, Dl, D2, and E, and calculation procedures Mark VI,
Mark VII, Perceived Noise Level, and Zwicker's Loudness Computation) when more
than 600 sounds were grouped according to spectral shape instead of according
to experimental study. Thus no overall advantage would accrue from regrouping
sets of data across studies on the basis of similar spectral shapes.
The relative efficacy of the eight descriptors in terms of variability was the
same as in Scharf, et. al. (1977) whether the sounds were grouped by spectrum
or by study. Mark VI, Mark VII, and Zwicker's procedures were the least variable
and the A-weighting was the most variable (C- and B-weightings having been ex-
cluded)—but the difference between the largest SD (2.8 dB for the A-weighting)
and the smallest SD (2.2 dB for Mark VI) was only 0.6 dB. However, although varia-
bility was not reduced when considered across all the nine spectral categories,
it was smaller across the eight descriptors for some categories than for others.
An interaction between descriptor and spectral shape was found to be statistic-
ally significant at the .001 level. Despite this significant interaction, the
present data do not reveal which descriptors are more suited than which others for
53
-------
specific spectral categories. More judgments of sound annoyance and noisiness
are needed, particularly for categories 1 (negative slope), 5 (U-shaped),
7 (low-frequency peaks and valleys), 8 (mid-to-high frequency peaks and
valleys), and 9 (mixed peaks and valleys) using a known calibrated standard
before this question can be answered.
Results obtained with a known, calibrated standard would provide
additional information that permits the computation of mean differences
as well as the standard deviations of the mean differences. Table IV showed
that regrouping data by spectral shape rather than by study resulted in
a larger reduction in both the SD and range of the mean differences for
the calculation systems than for the frequency-weighting functions. In
fact, such a regrouping of data enlarged the variability produced by the
A-weighting. These results are in line with earlier findings (Scharf, et. al.
1977) showing that the SDs produced by the frequency-weighting functions,
particularly the A-weighting, strongly depend on level whereas the calcula-
tion systems are less sensitive to level effects. Taken together, the
results from this report and Scharf, et. al. (1977) argue for the use of a
calculation procedure such as Mark VI to achieve a significant improvement in
predicting subjective magnitude from physical measurements. Further, the
greater flexibility provided by the calculation procedures offers a distinct
advantage should such factors as tonal components and duration need to be
incorporated into these systems.
54
-------
A detailed analysis of over 500 spectra with and without tonal compo-
nents provided little evidence for the need for a tone correction. This
outcome would appear to be at variance with previous conclusions in the
literature. However, the nature of the studies evaluated was such as to
reduce the likelihood of showing any effect of tonal components. Many of the
studies required loudness judgments or evaluative judgments at levels below
80 dB. Even those studies such as Ollerhead's (1971, 1973), which required
evaluative judgments at high levels, stressed noisiness as opposed to annoy-
ance. Studies by Berglund, et. al. (1975, 1976) suggest that at high
levels, noisiness and loudness are essentially indistinguishable, whereas
annoyance may remain considerably greater than both noisiness and loudness.
Subjects identify noisiness more as a characteristic of the sound and annoy-
ance more as a description of their own general reaction to noise. The
presence of tonal components at high levels may affect judgments of annoyance
more than they affect either noisiness or loudness. However, no measurements
seem to be available of "absolute" magnitude of annoyance caused by sound
with tonal components. Thus Ollerhead's subjects would probably have given
higher estimates of annoyance, had they been asked, than they did of noisi-
ness when exposed to high-level noise containing tonal components.
Given the small effect of tonal components in the present group of
studies, the evaluation of three different tone-correction procedures, FAR
36 (1969), Kryter and Pearson's (1965) and Stevens's (1970) could not lead to
definitive conclusions about their relative merits. Nevertheless, none
of the three improved the effectiveness of the descriptors to which they were
applied; the variability and the discrepancy between calculated and judged
level either remained the same or increased. This disappointing outcome
55
-------
should reinforce the realization that data are needed on a large enough set
of sounds with and without tonal components to permit adequate evaluation of
tone-correction procedures. Special attention must be paid to the instructions
given to th,e subjects. The present report has tended to distinguish studies
on the basils of a simple dichotomy, between loudness and evaluative judgments
such as noisiness, unacceptability, and annoyance. This dichotomy was neces-
sitated by the nature of the studies investigated which usually mixed together
a number of adjectives when giving instructions other than loudness. The
reports by Berglund, et. al. (1975, 1976) suggest that a careful distinction
should be made among loudness, noisiness, and annoyance in instructions. A
further important point is that most of the studies heretofore have used
psychophysical procedures that emphasise the overall level. Thus, observers
are asked to adjust one sound to be subjectively equal to another sound or to
report when one sound, presented at various levels, is subjectively greater
(or less) than a standard sound. Such a procedure is usually appropriate for
investigations of loudness but may inadvertently focus the subject on loudness
in a study that aims to investigate annoyance or even noisiness. Magnitude
estimation has been used successfully for judgments of sound annoyance by
Berglund, _et_. al. (1975, 1976), Bishop (1966), Galanter (1978), Hiramatsu,
et. al. (1976), and Scharf and Horton (1978). By presenting sounds with tonal
components at different tone-to-noise ratios, frequencies, and configurations,
an experimenter can obtain a fine grain scale of the relative annoyance of
various sounds. Such experiments would yield the kind of data needed to determine
when tonal corrections are needed and how best to implement them.
56
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APPENDIX A
CATEGORICAL ANALYSIS ACCORDING TO SPECTRAL TYPE
Introduction
Categorical analysis involved the identification and classification of
more than 600 spectra that were evaluated in a previous study (Scharf, Hellman,
and Bauer, 1977) . The spectra were obtained from 23 studies that encompassed
a wide variety of natural and simulated noises. In addition to the identifica-
tion and classification of spectra, a statistical analysis of subjective
measurements produced by the noises in each spectral category and across
spectral categories was made based on four frequency weighting functions (A,
Dl, D2, E) and four calculation procedures (Mark VI, Mark VII, Perceived
Noise Level, Zwicker).
Procedure
The spectra were subdivided into the following nine primary categories:
(1) negative slope, (2) positive slope, (3) broadband flat, (4) narrow band,
(5) U-shaped, (6) inverted U-shaped, (7) low-frequency peaks, (8) mid-to-
high-frequency peaks, and (9) mixed peaks. In order to obtain a finer analysis
of the data, category 1 (negative slope) was further divided into two parts, and
category 4 (narrow band) was divided into three parts.
Each of the nine categories and subcategories is defined as follows:
(1) Negative slope - maximum energy located at low frequencies.
(A) Strong negative slope - greater than 5 dB per octave fall-off
of energy above approximately 500 Hz, but fall-off often
begins between 100 and 1000 Hz.
A-l
-------
(B) Slight negative slope - noise energy falls off from 3 to 5 dB
per octave above 500 Hz, but fall-off often begins between
100 and 1000 Hz.
(2) Positive slope - maximum energy located at high frequencies. Noise
energy falls off rapidly below 500 Hz, but often the fall-off begins
at higher frequencies.
(3) Broadband flat - spectral distribution of energy remains about the
same (+5 dB) across a band of frequencies at least two octaves wide.
(4) Narrow band - octave band or narrower.
(A) Noise band centered at frequencies below 500 Hz.
(fi) Noise band centered at frequencies between 500 and 2000 Hz.
(C) Noise band centered at frequencies above 2000 Hz.
(5) U-shaped - noise energy reaches a maximum at low and at high fre-
quencies, i.e., the noise has a mid-frequency notch.
(6) Inverted U-shaped - noise energy falls off at low and at high
frequencies, i.e., the noise energy peaks over a broad range of
mid-frequencies.
(7) Low-frequency peaks - peaks and valleys in spectra (+5 dB) located
below 500 Hz.
(8) Mid-to-high-frequency peaks - peaks and valleys in spectra (+5 dB)
located above 500 Hz.
(9) Mixed peaks - peaks and valleys in spectra (+5 dB) located at
frequencies both below and above 500 Hz.
Table A-l shows the distribution of hoises according to spectral category
and type of noise. It is evident that the number of spectra are very unevenly
A-2
-------
TABLE A-l IDENTIFICATION OF SPECTRA ACCORDING TO SPECTRAL CATEGORY AND TYPE OF NOISE
NU
Category Aircraft Industrial
1A -
IB -
2 -
3 -
4A -
4B -
4C -
5 -
6 -
7 -
8 -
9 -
TOTAL
strong, negative 22 18
slight, negative 4
positive
broadband, flat 3
narrow band, centered
below 500 Hz
narrow band, centered
between 500 and 2000 Hz
narrow band, centered
above 2000 Hz
U-shaped
inverted U-shaped 15 14
low-frequency peaks
and valleys 5
mid-to-high frequency
peaks and valleys 32
mixed peaks and valleys 38 16
112 55
nioer ana iype
-------
divided according to categories. Categories IB (slight negative slope) and
3 (broadband flat) contain only eight spectra each and category 5 (U-shaped)
contains only six spectra. On the other hand, category 8 (mid-to-high-frequency
peaks and valleys) has 222 spectra, and category 9 (mixed peaks and valleys)
contains 104 spectra. Together, categories 8 and 9 contain over half the total
number of spectra. Table A-l also provides a breakdown by type of sound
(aircraft, industrial, etc.). The most striking concentration of spectral
shapes is in category 8 (mid-to-high-frequency peaks and valleys) which
contains 56% of the artificial spectra.
Evaluation of Subjective Measurements
A. Overall Evaluation
Within each spectral category noises were grouped according to whether
or not judged loudness levels were provided in the original study. In those
studies where loudness levels were available, it was possible to calculate
for each spectral category both mean differences between predicted and
observed loudness levels as well as standard deviations (variability measure).
Whenever loudness levels were not available, only standard deviations computed
from calculated levels could be obtained. For every category of spectra eight
overall values based on four different frequency-weighting functions (A, Dl,
D2, E) and four different calculation schemes (Mark VI, Mark VII, Perceived
Noise Level, Zwicker) were computed. The eight functions and schemes are
described in greater detail in Table II of Scharf, et. al. (1977).
Table A-2 shows the computations of standard deviations determined by
those studies that did not provide calibrated loudness levels. A total of
298 spectra from 11 studies listed in Table A-3 contributed to the values
A-4
-------
TABLE A-2 STANDARD DEVIATIONS (IN DECIBELS) COMPUTED FROM CALCULATED LEVELS
(Values were weighted within each category according to the number of spectra per study.)
Category
1A
IB
2
3
4A
4B
4C
I 5
6
7
8
9
- strong, neg. slope
- slight, neg. slope
- positive slope
- broadband, flat
- narrow-band, low frequency
- narrow-band, mid frequency
- narrow band, high frequency
- U-shaped
- inverted U-shaped
- low-frequency peaks
and valleys
- mid-to-high frequency
peaks and valleys
- mixed peaks and valleys
MEAN (unweighted) (in decibels)
Frequency Weighting
A Dl D2 E
2.
-
4.
-
3.
2.
2.
-
2.
1.
2.
2.
2.
8 2.7 2.6 2.9
- - -
1 3.3 3.3 3.3
_
6 1.1 2.3 1.7
4 2.2 2.3 1.7
8 3.2 3.0 2.2
- - -
8 2.3 2.5 2.2
5 1.5 1.5 1.6
4 1.8 1.7 1.7
1 2.0 1.8 1.8
7 2.2 2.3 2.1
Calculation Procedure
VI VII PNL ZWI
2.
-
3.
-
1.
2.
1.
-
1.
1.
1.
2.
1.
4
1
2
0
8
8
2
9
0
9
2
3
2
2
1
1
1
1
2
2
.8
-
.3
-
.2
.3
.9
-
.6
.0
.9
.1
.1
2.
-
3.
-
1.
2.
3.
-
2.
1.
2.
1.
2.
7 1.9
-
0 4.0
-
4 2.5
2 3.0
0 5.0
-
0 1.6
3 1.1
0 2.5
9 2.6
2 2.7
Number
of Spectra
27
0
12
0
13
10
12
0
22
53
106
43
298
Number
of SDs
7
0
1
0
1
1
1
0
5
6
6
6
34
-------
Table A-3 List of Studies that Contributed to Table A-2
No. SDs/study
2
3
1
1
2
2
1
1
1
2
1
Author
Borsky
Kryter
Pearsons and Bennett,
Pearsons and Bennett,
Peasons and Wells
Robinson and Bowsher
Wells (Aircraft)
Wells (Unpublished)
Wells 300
Wells 400
Wells UHV
Year
1974
1959
part 1 1969
part 3 1969
1969
1961
1970
c.1970
1969
1969
1972
No. Spectra/study
10
13
30
20
38
3*
29
30
39
58
25
*Same spectra judged twice, once for loudness and once for annoyance.
A-6
-------
shown in Table A-2. None of the 11 studies contained spectra for categories
IB (slight negative slope), 3 (broadband flat), and 5 (U-shaped). Further,
with the exception of the study by Robinson and Bowsher (1961) which provided
both equal-loudness and equal-annoyance •judgments, only equal-annoyance judg-
ments could be obtained from this group of studies.
Each value in Table A-2 is a weighted mean standard deviation. That is,
within each category the standard deviations for an individual study were
weighted according to the number of spectra per study. The criterion estab-
lished for inclusion of a group of sounds was a minimum of three spectra per
study per category. Moreover, whenever a study consisted of more than one
experiment, standard, or group of sounds, the standard deviation for each
part was determined separately before computing the weighted average for that
particular study. This added consideration is reflected in the column in
Table A-2 labeled "number of standard deviations". Therefore, except for
categories 2 (positive slope) and 4 (narrow-band noises), this number is
larger than the number of studies that contributed to the standard deviation
for a given category.
The method of averaging the results of a particular study may have an
important effect on the outcome. When a single overall standard deviation
is calculated across diverse portions of a study, such as differences in
procedures, standards, or type of spectra (artificial versus natural sounds),
the standard deviation is inflated. In addition to parts 1 and 3 of Pearsons
and Bennett (1969) that were kept separate in the analysis undertaken by
Scharf, et.al.(1977), the following studies were also divided into parts:
Borsky (1974), two parts; Kryter (1959), three parts; Pearsons and Wells
(1969), two parts; Wells 400 (1969), two parts.
A-7
-------
Finally, for each weighting or calculation procedure a mean standard
deviation (unweighted) determined across categories is shown in Table A-2.
The mean standard deviations (unweighted) and standard deviation of standard
deviations across spectral categories and across studies are presented in
Table A-4. The values calculated across studies were obtained from those
values in Scharf, et. al. (1977) that contributed to the spectral analysis
shown in Table A-2.
Table A-4 shows that regrouping the noises according to similar spectral
categories increases the mean standard deviations across weighting and
calculation procedures by an average of about 0.1 dB and decreases the stan-
dard deviation of standard deviations by an average of 0.2 dB. Thus, the
overall variability of these data is about the same whether they are grouped
according to study or according to spectral shape. However, regardless of
how these data are grouped, the A-weighting and Zwicker's scheme produce the
largest SDs and Mark VI produces the smallest SDs.
More information from Table A-2 can be obtained by evaluating the
results category by category. The outcome of such an evaluation is summarized
in Table A-5. According to Table A-5, of the nine categories for which
spectra are available, the A-weighting as well as Zwicker's scheme produce
the largest standard deviation for five out of nine categories. On the
other hand, Mark VI or Mark VII yield the smallest standard deviations for
seven of nine categories. (See Section II, Table III for a discussion of
the statistical analysis.)
A-8
-------
TABLE A-4
Mean Standard Deviations (in decibels) and Standard Deviation of Standard
Deviations (in decibels) across Spectral Categories and across Studies
(for which loudness levels were not available)
Frequency Weighting Calculation Procedure
A Dl D2 E VI VII PNL ZWI N*
Mean SD
(Unweighted)
1) across spectral 2.7 2.2 2.3 2.1 1.9 2.1 2.2 2.7 12
categories
2) across studies 2.5 2.1 2.1 2.2 1.9 2.0 2.1 2.4 11
SD of SDs
1) across categories .78 .75 .60 .62 .58 .64 .63 1.2 12
2) across studies 1.0 .92 .88 .95 .78 .79 .90 1.4 11
*Number of studies and parts or, number of spectral categories.
A-9
-------
TABLE A-5
Analysis of Standard Deviations (in Decibels) According to Categories
(Based on Calculated Levels)
Category
1A
2
4A
4B
4C
6
7
8
9
No. Spectra/No SDs
27/7
12/1
13/1
10/1
12/1
22/5
53/6
106/6
43/6
Largest SD
E
A, Zwicker
A
Zwicker
Zwicker
A, D2
A, D2, E
A, Zwicker
Zwicker
Smallest
Mark VI,
Mark VI,
Dl, Mark
SD
Zwicker
PNL
VI
E, Mark VI
Mark VI,
Mark VII,
Mark VII,
D2, E
D2, E
Mark VII
Zwicker
Zwicker
A-10
-------
Similarly, standard deviations were computed for each of the nine spectral
categories using data from the 10 studies, listed in Table A-6, that provided
loudness levels.
The results are shown in Table A-7. A total of 335 noises are distributed
across the nine spectral categories. More than one-third of the noises are
found in category 8 (mid-to-high-frequency peaks) and the lowest number are
found in category 4A (narrow band low-frequency noises).
Initially, standard deviations within a specific category were computed
across studies representing a wide range of loudness levels and mean differ-
ences. No attempt was made to group studies or spectra or to obtain an
actual weighted SD according to the number of spectra per study. This proce-
dure led to standard deviations as large as 6 dB for categories 1A (strong
negative slope) and 9 (mixed peaks) and as large as 5 dB for categories 4B
(narrow band mid-frequencies) and 8 (mid-to-high-frequencies). By combining
data across studies and computing a single standard deviation the possible
effect of spectral distribution of energy on standard deviations is obscured
by the very large variation among studies. A better assessment of variability
within categories is achieved by first calculating the standard deviation for
each individual study or group of individual spectra, averaging these standard
deviations for all studies within a given category and then calculating a
weighted or unweighted mean across spectral categories. This revised pro-
cedure was used for determining the within category standard deviations shown
in Table A-7- For the same reasons, i.e., to reduce to a minimum the within
and between study variations, it closely followed the procedure used to
describe the standard deviations indicated in Table A-2. The initial and
A-ll
-------
TABLE A-6 List of Studies that Contributed to Table A-7
No. Spectra/Study Study Year
18 Berglund, et. al_. 1976
105 Fishken 1971
10 Jahn 1965/66
8 Kryter and Pearsons 1963
31 Liibcke, et. al. 1964
30 Molino 1976
37 Quietzsch 1955
24 Rademacher 1959
39 Spiegel 1960
33 Yaniv 1976
A-12
-------
TABLE A-7 STANDARD DEVIATIONS (in decibels) COMPUTED FROM DIFFERENCES BETWEEN COMPUTED AND OBSERVED LOUDNESS LEVELS
(Standard deviations were first computed within each study and then weighted within a category according to
the number of spectra.)
Category
1A
IB
2 -
3 -
4A
4B
> 4C
I—*
w 5 -
6 -
7 -
8 -
9 -
- strong, neg. slope
- slight, neg. slope
positive slope
broadband flat
- narrow-band, low freq. noises
- narrow-band, mid freq. noises
- narrow-band, high freq. noises
U-shaped
-shaped
low-frequency peaks
mid-to-high frequency peaks
mixed peaks
A
3.8
3.7
3.95
3.5
3.4
1.5
1.9
3.7
3.2
1.4
3.0
1.8
We ight ing Scheme
Dl D2 E
3.
2.
4.
3.
3.
1.
2.
4.
3.
1.
4.
2.
5
3
2
2
3
6
2
2
2
2
0
5
3.6
3.4
4.2
3.2
3.3
1.6
2.1
4.1
3.3
1.3
4.0
2.4
3.5
2.4
4.4
3.3
3.4
1.5
2.8
4.0
3.2
1.1
3.7
2.2
Calculation Procedure
VI VII PNL ZWI
3.1
2.4
2.6
2.0
3.8
1.3
2.1
1.7
2.9
1.6
3.2
2.3
2.6
2.2
2.7
2.1
3.7
1.6
1.8
2.0
2.9
1.5
3.4
2.4
4.1
2.6
4.0
3.9
3.5
1.5
1.7
3.5
3.2
2.4
3.7
2.7
3.1
1.7
3.0
2.2
3.6
1.4
1.4
2.5
2.8
1.4
2.7
2.2
No.
Number SDs
37 5
8 2
10 2
8 2
5 1
12 3
6 1
6 2
46 7
20 4
116 12
61 15
Means (Unweighted) (N = 12)
(in decibels)
Means (Weighted according to
number of spectra )
(N = 335)
(in decibels)
2.9
2.8
3.
3.
0
2
3.0
3.25
3.0
3.1
2.4
2.7
2.4
2.75
3.1
3.3
2.3
2.5
Total N=335 noises
Means in Scharf, et . al . Table II,
corrected re: Appendix D, Table D-l
(Based on 20 studies) (in decibels)
3.05 2.65 2.73 2.63
2.26 2.22 2.6
2.
-------
revised procedures were the same for calculating the standard deviations
across categories.
Each value in Table A-7 for a specific spectral category and weighting
or calculation scheme is a weighted mean standard deviation. Within each
spectral category individual standard deviations were weighted according to
the number of spectra per study, provided the study had at least three
spectra. In some studies, spectra fell naturally into groups according to
such variables as signal-to-noise ratio or overall sound pressure level,
e.g., Lubcke, et_. al. (1964), Spiegel (1960), Fishken (1971), and Yaniv (1976).
Standard deviations were then computed for each grouping within a study.
On the other hand, whenever the number of spectra per study fell below the
minimum number of three, the results of more than one study or overall sound
pressure level were combined to produce a single estimate of the standard
deviation. Hence, as in Table A-2, the numbers in Table A-7 in the column
labeled "number of standard deviations" do not necessarily reflect the number
of studies that contributed to the standard deviations for a given category.
For this analysis, the number of standard deviations is sometimes less than
the number of contributing studies.
Compared to the initial procedure (i.e. computing a single estimate of
the standard deviation across studies within a spectral category), the revised
procedure (i.e., taking into account standard deviations for individual studies
or groups of spectra within a category before averaging) reduced substantially
the standard deviations computed both within and across categories. Only for
categories 4A (narrow band low frequency) and 4C (narrow band high frequency)
that are based on one standard deviation do the initial and revised procedures
yield the same result. Within categories 1A (strong negative slope), 4B
A-14
-------
(narrow band mid-frequency), 8 (mid-to-high-frequency peaks), and 9 (mixed
peaks), the revised procedure reduced the maximum standard deviation to 4.0 dB
The mean standard deviations (unweighted) and standard deviation of standard
deviations calculated across categories according to both the initial and
revised within category procedures are indicated in Table A-8. Also shown
are the mean standard deviations (unweighted) and standard deviation of stan-
dard deviations calculated across studies. Those values were obtained from
the standard deviations in Scharf, et. al. (1977) that contributed to the
spectral analysis shown in Table A-7.
According to Table A-8, the revised procedure reduces the mean standard
deviation across categories by an average of 0.8 dB for the four frequency-
weighting procedures and by an average of 1.1 dB for the four calculation
schemes. The mean standard deviation determined by the revised procedure is
about the same as the mean SD calculated across studies, but the SD of SDs
is about 0.2 dB smaller. Further, regardless of how these data are grouped,
the calculation schemes, with the exception of PNL, produce mean SDs about
0.5 dB smaller than the four frequency weightings.
A finer analysis of Table A-7 can be accomplished by examining the
results, spectral category by spectral category. The results are summarized
in Table A-9. In contrast to the results in Table A-5, the A-weighting fares
much better when loudness levels are provided. Only for categories 1A (strong
negative slope) and IB (slight negative slope) does the A-weighting yield
the largest SDs. For category 9, involving 61 spectra with mixed peaks, the
A-weighting produces the smallest SDs. On the other hand, the D1-, D2-, and
E-weightings produce the largest SDs for 6 out of 12 spectral categories.
Mark VI, Mark VII, and Zwicker calculation procedures perform about equally
A-15
-------
TABLE A-8
Comparison of Mean Standard Deviations (in Decibels) and Standard
Deviations of Standard Deviations (in Decibels) Across Spectral
Categories and Across Studies (Loudness Levels Provided)
Frequency Weighting Calculation Procedure
A Dl D2 E VI VII PNL ZWI N*
Mean SD
(Unweighted)
l)Across Categories
Initial Procedure
Revised Procedure
2)Across Studies
(Based on 10 studies)
3.7 3.9 3.9 3.8 3.5 3.5 4.0 3.6 12
2.9 3.0 3.0 3.0 2.4 2.4 3.1 2.3 12
3.2 3.0 3.1 2.9 2.5 2.4 2.9 2.3 16
SD of SDs
DAcross Categories
Initial Procedure 0.9 1.1 1.0 0.9 1.4 1.5 1.2 1.5 12
Revised Procedure 1.0 1.0 1.0 1.0 0.7 0.7 0.9 0.7 12
2)Across Studies 1.3 1.2 1.0 1.2 0.85 1.1 1.2 1.0 16
(Based on 10 studies)
*N = Number of studies and parts, or number of spectral categories.
LEGEND:
Initial Procedure: Within a specific category a single estimate of the
standard deviation was computed across studies.
Revised Procedure: Obtained first the standard deviation for each individual
study or group of individual spectra and then obtained a weighted mean within
a category.
A-16
-------
Table A-9
Analysis of Standard Deviations (in Decibels) According to Categories
(Loudness Levels Provided)
No. Spectra/
Category
1A
IB
2
3
4A
4B
4C
5
6
7
8
9
No. SDs
37/5
8/2
10/2
8/2
5/1
12/3
6/1
6/2
46/7
20/4
116/12
61/15
Largest SD
A, PNL
A
Dl, D2, E
PNL
Mark VI, Mark VIII
Dl, D2, Mark VII
E
Dl
D2
PNL
Dl, D2
PNL
Smallest SD
Mark VII
Zwicker
Mark VI, Ma
Mark VI, Ma
Zwicker
Dl, D2
Mark VI
Zwicker
Mark VI
Zwicker
Dl, E
Zwicker
A
A-17
-------
well producing the smallest SDs for 5 out of 12 categories. Mark VI and
Mark VII calculation procedures perform well for both groups of studies -
those that provided judged loudness levels and those that did not. (See
Section II, Table III on the spectral categories for a discussion of the
statistical analysis of these data).
In addition to an analysis of standard deviations within spectral cate-
gories, for those 10 studies that provided loudness levels it was also possible
to perform a within category analysis of mean differences between calculated
and observed levels. Table A-10 shows the results for each of the eight
frequency-weighting and calculation procedures and for the same 335, noises
upon which the standard deviations in Table A-7 are based. Each value for
a specific category and weighting or calculation scheme represents a weighted
mean difference. Within a category the mean differences for an individual
study were weighted according to the number of spectra per study. The mean
differences calculated across categories, the standard deviations of the
means, and the range of mean differences for each weighting and calculation
scheme are also indicated in Table A-10*.
Table A-10 suggests that the A-weighting produces the largest mean
difference, the largest standard deviation, and the largest range of mean
differences. The smallest overall mean difference is produced by Mark VI
and Perceived Noise Level calculation procedures. Zwicker's procedure
produces the smallest standard deviation as well as the smallest range of
mean differences. The differences between Zwicker's procedure and Mark VI
*Note that, whereas the means within categories are weighted values, the
means calculated across categories are unweighted.
A-18
-------
Table A-10
CALCULATED MINUS OBSERVED LOUDNESS LEVEL (in decibels)
Category
1A
IB
2 -
3 -
4A
4B
4C
5 -
6 -
7 -
8 -
9 -
- strong, neg. slope
- slight, neg. slope
positive slope
broadband flat
- narrow-band, low freq. noises
- narrow-band, mid freq. noises
- narrow-band, high freq. noises
U-shaped
inverted U-shaped
low-frequency peaks
mid to-high frequency peaks
mixed peaks
A
-15.
-18.
-14.
-16.
-11.
-1.
-9.
-16.
-13.
-10.
-4.
-12.
Frequency
Dl
4
1
0
7
5
96
9
4
6
4
8
3
-8.2
-10.5
-5.8
-9.9
-3.2
-0.83
-0.63
-7.95
-8.0
-5.0
+2.1
-5.9
Weighting
D2 E
-10.0
-11.7
-5.4
-10.0
-5.6
-0.56
-0.47
-7.9
-8.3
-6.0
+2.1
-6.2
-9.8
-12.6
-6.8
-11.9
-4.3
-1.46
-2.07
-9.25
-9.8
-6.3
-0.04
-7.8
Calculation
VI VII
-2.5
-6.5
-0.82
-4.0
-2.9
+3.56
-0.27
-2.8
-2.9
-0.8
+5.1
+0.62
-10.1
-12.9
-9.3
-11.4
-10.7
-4.65
-7.97
-10.6
-10.2
-6.2
-1.9
-6.7
Procedure
PNL ZWI
-2.6
-5.1
-2.2
-3.9
-2.1
+2.0
+1.2
-4.0
-2.6
-2.7
+5.7
-0.11
+3.7
-0.15
+4.0
+1.1
-0.02
+6.7
-0.8
+0.1
+2.6
+5.8
+8.0
+5.9
Number
of Spectra
37
8
10
8
5
12
6
6
46
20
116
61
Mean (unweighted)
SD
Range
-12.
4.
16
1
8
-5.3
4.0
12.6
-5.8
4.3
13.7
-6.8
4.1
12.6
-1.2
3.2
11.6
-8.6
3.2
11.1
-1.4
3.1
10.8
+3.1
3.0
8.8
TOTAL
335
-------
and Perceived Noise Level are so small that they are probably not statistically
significant. Moreover, in contrast to Table IV of Scharf, et. al. (1977) which
suggests that the standard deviation of mean differences across the same eight
frequency-weighting and calculation procedures varies between 4 and 5 dB,
regrouping the data on the basis of spectral categories reduces the standard
deviation of means for the calculation procedures to an average value of 3.1 dB.
This value is about 1.2 dB smaller than the standard deviation of means computed
for the four frequency weightings. Due to the large differences in number of
spectra that contributed to the weighted mean differences among the nine spectral
categories, a meaningful, statistical analysis of these data could not be
accomplished. Nevertheless, they do suggest that regrouping the data into
similar spectral categories produces an advantage to the four calculation
procedures but not to the four frequency-weighting functions.
A more detailed analysis of Table A-10 can be obtained by evaluating the
results category by category, as summarized in Table A-ll. Table A-ll shows
that the A-weighting consistently underestimates the subjective magnitude of
noise for most categories of spectra, i.e., it produces the largest mean
difference for 10 out of 12 categories. For the remaining two categories
(4B, narrow band mid-frequency; 8, mid-to-high-frequency peaks), Zwicker's
procedure produces the largest mean difference. On the other hand, Mark VI
produces the smallest mean difference for six out of the 12 categories. The
results in Tables A-10 and A-ll, together with the analysis of Tables A-2
and A-7, indicate that the current ANSI standard (1972), Mark VI, is probably
most generally suitable for predicting the loudness or noisiness of noise,
despite the small differences between Mark VI and the other descriptors
evaluated.
A-20
-------
Table A-11
Analysis of Mean Differences According to Categories
(Loudness Levels Provided)
Category
1A
IB
2
3
4A
4B
4C
5
6
7
8
9
No. Spectra/
No . Me an D i f f s .
37/14
8/3
10/4
8/3
5/3
12/8
6/3
6/2
46/7
20/5
116/15
61/20
Largest
Mean Dif f s .
A
A
A
A
A
Zwicker
A
A
A
A
Zwicker
A
Smallest
Mean Diffs.
Mark VI, PNL
Zwicker
Mark VI
Zwicker
Zwicker
Dl, D2
Mark VI
Zwicker
Mark VI, PNL,
Zwicker
Mark VI
Dl, D2, E
Mark VI, PNL
A-21
-------
B. Effect of Tonal Components on Analysis of Categories 7, 8, and 9
The categorical analysis described in Section II also permits a preliminary
assessment of the need for a tone correction procedure to be applied to the
existing weighting and calculation procedures. Table A-l indicates that about
two-thirds of the stimuli evaluated are contained within categories 7, 8, and
9 (low-frequency, mid-to-high-frequency, and mixed peaks, respectively). A
more detailed analysis of these spectra was performed to determine (1) what
proportion of spectra in each spectral category included tonal components,
(2) whether within a category those spectra with tonal components produce a
larger variability and larger mean differences than do those spectra without
tonal components, and (3) whether a specific frequency-weighting or calculation
procedure was more suited than another for predicting the perceived magnitude
of noise-tone complexes. Within each category, noises were grouped according
to whether or not loudness levels were provided in the original study.
Table A-12 and A-13 provide two sets of weighted standard deviations for
categories 7, 8, and 9; within each category one set of SDs is for spectra
that contained peaks and valleys both with and without tones, and the other
set for such spectra without tones. Category 9 in Table A-12 includes an
additional set of standard deviations with tones. The presence of tonal
components was based on criterion developed for the tone-correction procedures
described in section III.
Table A-12 and A-13 show that most of the sounds in categories 7 and 8
contained tonal components. Owing to the large differences in the number of
spectra in the total groups and the groups without tones, a comparison of
SDs is inappropriate. (The larger the n, the larger the SD tends to become.)
A-22
-------
Table A-12
Standard Deviations (in Decibels) Computed from Calculated Levels
for Categories 7, 8, and 9. (Loudness Levels not Measured in
Original Studies. Values were Weighted within Each Category
According to the Number of Spectra Per Study)
Frequency Weighting Calculation Procedure
Number
Category Spectra A Dl D2 E VI VII PNL ZWI
7 53 1.5 1.4 1.5 1.5 1.2 1.1 1.3 1.1
(with and
without tones)
7 1.65 1.1 1.4 1.2 0.6 0.6 0.5 1.1
(without Tones)
8 106 2.4 1.8 1.7 1.7 1.9 1.9 2.0 2.5
(with and
without tones)
20 1.7 1.8 1.8 1.6 1.3 1.5 1.8 1.4
(without tones)
9 43 2.1 2.0 1.81.8 2.0 2.1 1.9 2.6
(with and
without tones)
* 21 1.3 1.1 1.2 0.85 0.83 0.95 1.0 1.4
(without tones)
* 18 3.5 2.6 2.25 2.4 2.4 2.5 2.5 2.7
(with tones)
*Two spectra were not included in this analysis because they did not satisfy
the criterion of at least three spectra per study required for computation
of a standard deviation.
A-23
-------
Table A-13
Standard Deviations (in Decibels) Computed from Differences
Between Computed and Observed Loudness Levels for Categories
7, 8, and 9 (Values were Weighted within Each Category
According to the Number of Spectra Per Study)
Frequency Weighting Calculation Procedure
Number
Category Spectra
A Dl D2 E
VI VII PNL ZWI
7 20
(with and
without tones)
14
(without: tones)
1.4 1.2 1.3 1.1 1.6 1.5 2.4 1.4
1.3 1.4 1.4 1.2 1.3 1.6 2.4 1.7
8 116
(with and
without tones)
3.0 4.0 4.0 3.7 3.2 3.4 3.7 2.7
10
(without tones)
2.7 2.9 2.8 2.5 2.2 2.8 2.5 2.1
61
(with and
without tones)
1.8 2.5 2.4 2.2 2.3 2.4 2.7 2.2
51
(without tones)
21 2.8 2.7 2.6 2.5 2.8 2.8 2.4
A-24
-------
Only in category 7 for loudness levels (Table A-13) can a comparison be made,
and there the 14 spectra without tones tended to give slightly larger SDs for
5 of the 8 descriptors than did the 20 spectra with and without tones. How-
ever, the overall difference of 0.2 dB is not meaningful. Category 9 provides
a more even distribution for those sounds judged with respect to an evaluative
attribute (Table A-12). There the SDs are larger by about 1.5 dB for the 18
sounds with tones than for the 21 sounds without. This finding suggests,
quite tentatively, that in judgments of noisiness, unacceptability, etc., tonal
components may increase the variability of the descriptors for spectra that
contain mixed peaks and valleys.
A-25
-------
APPENDIX B
"ANOMALOUS" DATA
The term anomalous data is used as short hand for the six studies in
Scharf, et. al. (1977) that produced the largest SDs (see Scharf et. al.,1977,
Table II). A closer examination of those studies reveals characteristics
that distinguish them from the average of the 20 studies and especially from
those studies that yielded the smallest SDs.
Table B-l shows the standard deviations produced by the six anomalous
studies and those produced by all 20 studies. For every descriptor, the
average standard deviation from the six studies is not only larger than from
the entire group of studies, but the disparity is larger by about 0.5 dB for
the six weighting functions than for the five calculation procedures.
Table B-2 provides a comparison between the six anomalous studies and
the six studies that produced below average standard deviations. Values are
given for eight descriptors; B, C, and PNLC are omitted. The mean standard
deviation from the anomalous studies is about 2 dB larger than from the least
variable studies. The average standard deviation for the weighting functions
is about 0.5 dB larger than that for the calculation procedures. An examina-
tion of the less variable studies show that they share the following charac-
teristics: a) the spectra tend to be fairly homogeneous; b) the stimuli are
exclusively natural, as opposed to artificial, sounds; c) the range of sound
pressure levels in a study is less than 25 dB; d) the standard deviations are
based on a single set of measurements or experimental conditions.
On the other hand, those studies that produced unusually large SDs
differed from the least variable studies in at least one of the characteristics
indicated below.
B-l
-------
Table B-l
Standard Deviations (in Decibels) from
Six Studies Yielding the Greatest Variability
Study Frequency Weighting Calculation Procedure
A B C Dl D2 E VI VII PNL PNLC ZWI
Fiahken (1971)
84/12* 2.7 2.9 3.0 3.9 3.9 3.6 2.9 2.8 3.8 3.6 2.5
21/3* 4.5 4.6 4.6 4.4 4.4 4.4 4.4 5.4 3.4 3.5 3.7
Pearsons and Bennett
(part 1, 1969)
30/30 4.3 4.5 4.7 3.5 3.7 3.3 2.8 2.8 2.9 2.2 3.7
Pearsons, _et_.^. (1968)
108/54* 6.5 5.1 5.3 2.5 2.8 3.0 2.2 2.2 3.0 2.6 2.1
Spiegel (1960)
20/20 4.7 6.2 6.8 4.2 4.0 4.2 2.4 1.9 3.2 3.7 2.4
20/20 5.3 4.9 5.1 3.5 4.1 3.6 2.6 2.6 2.9 3.2 3.0
Quietzsch (1955)
27/27 4.2 4.4 5.7 4.0 4.3 4.2 3.1 3.2 4.0 4.2 3.3
10/10 3.8 6.3 7.0 3.3 2.9 3.8 2.5 2.5 2.6 2.8 2.5
Wells 300-400 (1969a)
300- 42/42 3.7 5.2 6.6 2.4 2.7 2.1 2.1 2.2 2.3 2.4 5.3
400- 60/60 2.5 4.2 4.9 2.5 2.0 2.6 2.5 2.6 2.5 1.8 3.1
X 6 Studies
(N = 10) 4.2 4.8 5.4 3.4 3.5 3.5 2.8 2.8 3.1 3.0 3.2
X 20 Studies
(N = 28) 3.1 3.6 4.2 2.7 2.7 2.6 2.3 2.2 2.6 2.7 2.4
Scharf, et.al.1977 Table II,
corrected re: Appendix D, Table D-l
* The number in front of the slash is the number of conditions (e.g. different sound
pressure levels, instructions, etc.)
** N = number of standard deviations
B-2
-------
Table B-2
Standard Deviations (in Decibels) from
Six Studies that Produced the Smallest Variability
Frequency Weighting Calculation Procedure
Study A Dl D2 E VI VII PNL ZWI
Jahn (1965/66)
10/10 1.3 1.2 1.3 1.2 0.9 0.9 1.0 0.8
Pearsons and Bennett
(1969, part 3)
20/20 1.7 1.4 1.4 1.7 1.3 1.5 1.3 1.8
Robinson and Bowsher
(1961)
1.9 1.4 1.5 1.9 1.2 1.6 1.1 0.9
Wells (1970)
1.6 1.2 1.3 0.9 1.2 1.2 1.3 2.2
Wells (Unpublished)
(1970) 111 1.3 1.3 1.1 0.9 0.9 1.2 1.1
Wells (UHV) (1972) 1.5 1.3 1.5 1.3 1.1 1.0 1.3 0.9
X 6
(N =
studies
6)
1.5 1.3 1.4 1.4 1.1 1.2 1.2 1.3
X 6 anomalous studies
(N = 10) 4.2 3.4 3.5 3.5 2.8 2.8 3.1 3.2
B-3
-------
Characteristics of Anomalous Studies
a) The spectra tend to be heterogeneous.
Pearsons, et_._ _aL._ (1968, 1969)
Quietzsch (1955)
Spiegel (1960)
b) The spectra include only artificial sounds.
Fishken (1971)
Pearsons and Bennett, Part I, (1969); Pearsons, et. al. (1968, 1969)
Spiegel (1960)
Wells 300-400 series (1969a)
c) The range of levels is large
Fishken (1971)
Quietzsch (1955)
d) The standard deviations are based on more than one set of experi-
mental conditions or measurements.
Fishken (1971)
Pearsons, et. al. (1968, 1969)
These characteristics suggest under what conditions a group of sounds
is likely to be less well assessed by the descriptors.
A detailed analysis of five of the six anomalous studies follows.
Spiegel (1960)
Spiegel's (1960) study illustrates how averaging data produced by
heterogenous spectra inflates standard deviations. Spiegel studied 20
noises distributed across six spectral categories (2 (positive slope), 4A
(narrow band low-frequency), 4B (narrow band mid-frequency), 4C (narrow band
B-4
-------
high-frequency), 5 (U-shaped) and 6 (inverted U-shaped)). Measurements were
made at two loudness levels, 64 phons and 85.5 phons. The standard deviations
computed separately for each spectral category produce an average value
smaller than the single standard deviation computed for all 20 noises, as in
Table B-l. Table B-3 presents a re-evaluation of Spiegel's study. Both sets
of mean standard deviations, weighted and unweighted, are considerably smaller
than the overall mean standard deviations shown in Table B-l.
Recomputing the mean differences between observed and calculated loudness
levels by first calculating the means for a given category and then computing
the overall means only slightly reduces the overall mean differences.
Wells 300 series (1969a)
The measurements by Wells provide another example of the way in which
homogeneous grouping of spectra can reduce SDs. Wells's 300 series comprised
mainly octave-band noises both with and without tones. The large SDs in
Table B-l can be ascribed to heterogeneity of spectra both across and within
categories.
The first source of variability can be reduced by computing the SDs
separately for each spectral category before obtaining the overall average
standard deviation. Table B-4 shows that the mean standard deviations
(weighted or unweighted) computed across categories are smaller by about
0.5 dB than the previously determined average values. The A-weighting and
Zwicker's procedure show the largest reductions. The A-weighting does least
well for narrow-band, low-frequency noises, and Zwicker's procedure is poorest
for narrow-band, high-frequency noises. Further, with the exceptions of the
A-weighting, Mark VI, and Mark VII, the SDs tend to be larger for category
4C which consists of high-frequency noises than for categories 4A and 4B.
B-5
-------
Table B-3
Spiegel Study (Standard Deviations in Decibels)
Frequency Weighting
A Dl D2 E
Calculation Procedure
VI VII PNL ZWI
CAT.
2
2
4a
4a
4b
4b
4c
4c
5
5
6
6
LL
64
85
64
85
64
85
64
85
64
85
64
N
2
2
2
2
3
3
2
2
3
3
4
85 4
(N=32)
0.31
1.4
0.58
0.84
1.9
2.1
3.7
0.21
4.3
3.1
3.5
6.1
0.51
1.2
0.41
1.0
2.0
2.3
3.8
0.25
4.7
3.6
2.6
4.0
0.47
1.3
0.53
0.88
2.0
2.4
3.9
0.31
4.7
3.5
2.3
5.1
0.46
1.3
0.44
0.97
1.8
2.2
4.0
0.43
4.6
3.3
2.8
3.8
0
1,
0.
0.
1.
1.
3.
0.
2.
0.
2.
3.
.54
.4
,60
,89
4
,6
I
22
6
72
7
7
0.01
1.3
0.70
1.06
1.5
2.0
2.2
0.55
2.5
1.4
1.9
3.7
0.25
1.4
0.25
1.34
1.65
2.1
3.4
0.33
4.5
2.5
2.4
4.1
0.45
1.0
0.20
1.49
1.60
2.2
1.4
2.0
3.4
1.5
2.7
4.0
X, unweighted across categories
64
85
16
16
X, weighted across
X, from
64
85
Table
64
85
16
16
B-l
20
20
2.4
2.3
categ
2.6
2.8
4.7
5.3
2.3
2.1
;ories
2.5
2.4
4.2
3.5
2.3
2.2
2.0
2.1
4.0
4.1
2.4
2.0
2.5
2.3
4.2
3.6
1.
1.
2.
1.
2.
2.
8
4
0
7
4
6
1.5
1.7
1.6
1.9
1.9
2.6
2.1
2.0
2.2
2.3
3.2
2.9
1.6
2.0
1.9
2.3
2.4
3.0
B-6
-------
Table B-4
Wells 300 Series (Standard Deviations in Decibels)
Frequency Weighting Calculation Procedure
A Dl D2 E VI VII PNL ZWI
N
Category
4a 13 3.6 1.1 2.3 1.7
4b 10 2.4 2.2 2.3 1.7
4c 12 2.8 3.2 3.0 2.2
"X SD
(unweighted) 2.9 2.2 2.5 1.9
X SD
(weighted) 3.0 2.1 2.5 1.9
1.2 2.2 1.4 2.5
2.0 2.3 2.2 3.0
1.8 1.9 3.0 5.0
1.7 2.1 2.2 3.5
1.6 2.1 2.2 3.5
X
from Table B-l
42 3.7 2.4 2.7 2.1 2.1 2.2 2.3 5.3
B-7
-------
A further reduction in standard deviations can be obtained by subdividing
spectra within a category into two groups, one with tones and another without
tones. The results of this analysis for an arbitrarily chosen subgroup of 20
of Wells's spectra are presented in Table B-5 together with an analysis of
results for categories 4A and 4C. The, overall analysis shows that, for seven
out of eight descriptors, spectra with pure tones produce larger standard
deviations than spectra without tones. Similarly, for categories 4A and 4C
the presence of pure tones enlarges standard deviations for six of the eight
descriptors.
Wells 400 series (1969a)
The Wells 400 series can be analyzed in the same way as the Wells 300
series. Wells's 400 series consisted mainly of broadband noises that con-
tained either single or multiple pure tones. Of the 60 noises, 57 fell into
categories 7, 8, and 9 (low-frequency, mid-to-high-frequency, and mixed peaks,
respectively). The relatively large SDs in Table B-l can be ascribed to the
presence of multiple and single pure tones as well as to the heterogeneity of
spectra across categories. It is possible, for example, to subdivide the
spectra of the Wells' 400 series into two groups, one that consisted of noise-
tone complexes with single tones and another that consisted of noise-tone
complexes with multiple tones. The results of this analysis for six spectra
that contained multiple pure tones and for 12 arbitrarily chosen spectra that
contained single tones are shown in Table B-6. With the exception of Zwicker's
procedure, the presence of multiple pure tones produces larger calculated SDs
than the presence of single tones.
B-8
-------
Table B-5
Wells 3001 Series Comparison of SDs (in Decibels) Produced by
Octave-Band Noises With and Without Tones
Frequency Weighting
A Dl D2 E
Calculation Procedure
VI VII PNL ZWI
N
With Tones 9 5.2 2.9 3.8 2.5
Without Tones 11 3.5 1.6 2.5 0.9
Cat. 4A
With Tones 4 5.5 0.7 3.1 2.4
Without Tones 3 3.4 0.3 1.7 0.9
Cat 4C
With Tones 3 2.8 4.8 5.0 3.5
1.3 2.8 3.2 6.2
2.2 1.8 1.9 3.9
0.24 2.9 0.5 2.8
0.7 0.9 0.7 1.7
1.4 3.4 4.9 7.0
Without Tones
1.6 1.0 1.6 3.3
B-9
-------
Table B-6
Wells 400 Series. Comparison of SDs (in Decibels) Produced by
Wide-Band Noises with Single and with Multiple Pure Tones
Frequency Weighting Calculation Procedure
A Dl D2 E VI VII PNL ZWI
N
Single Tones 12 1.6 1.4 1.2 1.2 1.6 1.6 1.5 2.0
Multiple Tones 6 2.7 3.6 3.0 3.5 2.0 2.3 2.9 1.8
X
(Weighted) 18 2.0 2.1 1.8 2.0 1.7 1.8 2.0 1.9
B-10
-------
The variability across categories can be reduced by computing the stan-
dard deviation for each category separately before computing the overall SD.
Table B-7 shows the results of this analysis as well as the previously calcu-
lated estimate of the standard deviation for the Wells 400 series. Two features
of Table B-7 are of interest. First, the calculation of a single estimate of
the standard deviation across diverse portions of a study enlarges slightly
the standard deviation. Second, as suggested by the Wells 300 series, those
spectra that only contain low-frequency tonal spikes produce smaller standard
deviations than do those spectra that contain tonal spikes above 500 Hz. The
A-weighting and Zwicker's procedure produce the largest standard deviations
for category 8 (mid-to-high-frequency peaks), and Zwicker's procedure also
produces the largest standard deviation for category 9 (mixed peaks).
Quietzsch (1955)
Quietzsch's results cannot be analyzed in the same straightforward
manner as those of Spiegel or Wells because his noises varied widely in
spectral shape as well as in amplitude. The 37 noises varied from 47 to
98 dB overall sound pressure level and 49 to 106 phons loudness level. Thus,
categorizing the sounds according to spectral shape and computing the standard
deviation separately for each category has only a small effect on the overall
mean standard deviation. In order to evaluate Quietzsch's results it is
necessary to determine more exactly the effect of sound pressure level
on standard deviations. However, his results have too few noises at each
level to make this determination. The specific effect of sound pressure
level on SDs will be demonstrated in the section on Fishken's measurements.
B-ll
-------
Table B-7
Wells 400 Series (Standard Deviations in Decibels)
Frequency Weighting Calculation Procedure
A Dl D2 E VI VII PNL ZWI
N
Category
7 18 1.8 2.2 1.8 2.2 1.4 1.3 1.6 1.3
8 36 2.8 2.1 1.8 2.3 2.4 2.6 2.0 3.2
9 3 1.9 2.8 1.8 3.3 3.4 4.2 3.4 4.7
X SD
(Unweighted) 2.2 2.4 1.8 2.6 2.4 2.7 2.3 3.1
X SD
(Weighted) 2.4 2.2 1.8 2.3 2.1 2.3 1.9 2.7
X
from Table B-l 60 2.5 2.5 2.0 2.6 2.5 2.6 2.5 3.1
B-12
-------
Pearsons and Bennett (1969)
Pearsons' and Bennett's data, part 1, produced above average standard
deviations whereas part 3 produced below average standard deviations. The
range of noise levels in parts 1 and 3 is nearly the same, and the noises
are distributed among the same number of spectral categories. Parts 1 and
3 appear to differ only in that Part 1 consists exclusively of artificial
noises whereas part 3 consists exclusively of natural noises.
Table B-8 shows that artificial noises produced larger SDs than did natural
noises. In addition, consistent with the results of the Wells 300-400 series,
those spectra that contain only low-frequency tonal spikes produced the lowest
SDs.
Further evidence tha' -w-frequency tonal spikes produce smaller standard
deviations than mixed low- a^A high-frequency spikes can be obtained from a
within-category analysis of spectra from Pearsons and Bennett part 1, category
2. The 12 spectra in this category of noises that produced a positive slope
were divided into two equal subgroups. One group consisted of six noises
that contained a low-frequency tonal spike while another group consisted of
six noises that contained both a low- and a high-frequency tonal spike. The
standard deviations were computed separately for each group. The results are
indicated in Table B-9.
Table B-9 shows that, except for the A-weighting, those noises with low-
frequency spikes produce smaller standard deviations than those noises with
low- and high-frequency spikes. The largest difference in standard deviation
between the two groups is produced by the Perceived Noise Level procedure.
Table B-9 also shows that the computation of a single standard deviation
acorss diverse portions of a study within a category enlarges the mean stan-
dard deviation by about 1.5 dB.
B-13
-------
Table B-8
Pearsons and Bennett (Standard Deviations in Decibels)
Frequency Weighting Calculation Procedure
N A Dl D2 E VI VII PNL ZWI
Category
6,
6,
7,
7,
9,
9,
part
part
part
part
part
part
1
3
1
3
1
3
7
5
5
2
6
6
3.8
1.2
1.8
1.5
3.5
1.5
2.8
0.9
2.1
0.05
3.4
1.1
3.2
1.0
2.2
0.6
3.5
1.1
2.5
0.7
2.0
0.4
3.3
1.0
1.8
0.9
0.9
0.3
3.1
1.5
1.6
0.8
0.7
0.4
2.9
1.6
2.2
1.1
0.9
0.09
3.5
1.3
1.5
0.9
1.5
0.7
3.1
2.5
B-14
-------
Table B-9
Pearsons and Bennett, Part 1 (Standard Deviations in Decibels)
Frequency Weighting Calculation Procedure
A Dl D2 E VI VII PNL ZWI
N
Category 2
Group I
Low-fre quency
spikes 6 2.2 2.0 1.9 1.8 1.5 1.5 1.6 1.7
Group II
High-frequency
spikes 6 2.1 2.1 2.1 2.1 1.9 2.0 2.2 2.1
X 2.15 2.05 2.0 1.95 1.7 1.75 1.9 1.9
Single SD
computed
across category 4.1 3.3 3.3 3.1 3.1 3.3 3.0 4.0
B-15
-------
The standard deviations across weighting and calculation procedures for
Pearsons and Bennett, part 1, may be reduced about 1.1 dB by computing the
standard deviation for each of the four spectral categories separately
before computing a mean SD across categories. This procedure also reduces
the overall SDs produced for Pearsons and Bennett, part 3, but the decrease in
standard deviations is smaller than for part 1. Nevertheless, the discrepancy
between the standard deviations produced by parts 1 and 3 remains about 1.2 dB,
suggesting that the difference in SDs produced by artificial and natural noises
is not easily eliminated.
Fishken (1971)
Fishken measured the overall loudness of broadband noise with tonal spikes
in two separate series of experiments. In the first series, the overall SPL
of the tone and noise was held constant at one of seven overall sound pressure
levels between 30 and 90 dB. At a given overall sound pressure level, both
the frequency of the tone or tonal complex and the tone-to-noise ratio were
varied. Four different tones or tonal complexes were combined with three
different tone-to-noise ratios so that a given experimental session consisted
of 12 different tone and noise combinations. The second series of experiments
by Fishken consisted of three parts. In each part the tone-to-noise ratio and
the frequency of the tonal complexes were held constant but the overall sound
pressure level of the tone and noise was varied in 10-dB steps over a range
of seven levels between 30 and 90 dB. The frequency evaluations for tonal
complexes concern those measurements of a pair of 500-Hz and 2000-Hz tones
added to a broadband noise. The results of both series are evaluated with
respect to each of the following variables: a) frequency of tone, b) tone-to-noise
ratio, c) overall sound pressure level of the tone and noise complex.
B-16
-------
a) Frequency of Tone
The analysis of results by Wells (1969a) and by Pearsons and Bennett
(1969) which were based on annoyance judgments showed that the presence of
low-frequency tonal spikes produced smaller SDs than the presence of high-
frequency spikes. A reevaluation of the first series of experiments by
Fishken (1971) indicates that loudness judgments produce a similar outcome.
Two sets of standard deviations were obtained, one that omitted the 500-Hz
data and another that omitted the 4000-Hz data. These results are shown in
Table B-10 together with the standard deviations previously calculated (see
Table II, Scharf, et. al. 1977 and Appendix D, Table D-l, this report) for
the entire group of 84 stimuli. To minimize the possible effect of sound
pressure level on SDs, each value was obtained by first computing the SD at
each level and then averaging the results across levels.
Table B-10 suggests that, unlike the results of the Wells (1969a) 400
series based on annoyance judgments, the SDs produced by the A-weighting
and Zwicker's procedure do not depend on sound frequency when results are
based on loudness judgments. Five procedures (Dl, D2, E, Mark VI.and Per-
ceived Noise Level), however, do appear sensitive to a high-frequency spike,
i.e., the SDs are reduced when the 4000-Hz data are omitted suggesting that
the presence of a 4000-Hz tone inflates the SDs. The opposite occurs for
a tone at 500 Hz. With the exception of the A-weighting and Zwicker's
procedure, the SDs produced by the remaining six procedures are larger when
the 500-Hz tone is ommitted. The results at 500 Hz suggest, in agreement
with the outcome for annoyance, that the presence of a 500-Hz tone decreases
the overall standard deviations.
B-17
-------
Table B-10
Fishken (First Experimental Series). Effect of Frequency of
Tone on Standard Deviations (in Decibels)
Frequency Weighting Calculation Procedure
A Dl D2 E VI VII PNL ZWI
_N
SD Scharf,
e_t.al. ,1977
(Corrected)
Table II 84 2.7 3.9 3.9 3.6 2.9 2.8 3.8 2.5
SD without
4000-Hz Tone 63 2.8 3.3 3.2 3.0 2.8 2.9 3.5 2.9
SD without
500-Hz Tone 63 2.8 4.4 4.4 4.0 3.2 3.2 4.3 2.7
B-18
-------
The variability of loudness judgments produced by tone and noise does
not show directly how the presence of a tone may alter the overall judgment
of loudness. To answer this question, it is necessary to examine mean differ-
ences between predicted and measured loudness levels. Therefore, mean differ-
ences, computed for the same series of measurements that contributed to Table
B-10, are shown in Table B-ll.
According to Table B-ll, the mean differences calculated by Zwicker's
procedure are independent of frequency. Moreover, a tone at 500 Hz heard
together with noise has very little effect on the calculated mean differences,
whereas the removal of a 4000 Hz tone has a more noticeable effect. When
the 4000 Hz tone is omitted, the mean differences approach zero more closely
for the Dl and D2 frequency-weighting functions and for the Mark VI and
Perceived Noise Level calculation procedures. Taken together, SDs and
calculated mean differences show that, except for Zwicker's procedure, the
descriptors predict results less well when a 4000 Hz tone is added to broad-
band noise than when a 500 Hz tone is added.
b) Tone-to-Noise Ratio
The available evidence (Little, 1961; Pearsons, et. al., 1968) suggests
that, when single and multiple tones are introduced into bands of noise at
tone-to-noise ratios of +15 dB and greater, the sounds become more annoying
than the perceived level predicted by any frequency-weighting or calculation
scheme. The same 84 stimuli of Fishken (1971) were regrouped to determine
whether this effect of tone-to-noise ratio on annoyance also obtains for
loudness. Table B-12 shows the effect of tone-to-noise ratio on calculated
SDs and Table B-13 shows the effect on mean differences.
B-19
-------
Table B-ll
Fishken (First Experimental Series)
Effect of Frequency of Tone on Mean Differences
(Calculated Minus Observed Loudness Levels, in Decibels)
Frequency Weighting Calculation Procedure
A Dl D2 E VI VII PNL ZWI
N
Mean Differences
Scharf, et^.a^. ,
1977 (TabTe~Tv) 84 -4.8 +2.1 +2.0 +0.3 +4.9 -1.9 +5.5 +7.8
Mean Differences
without
4000-Hz Tone 63 -5.2 +0.7 +0.6 -0.9 +4.1 -2.6 +4.2 +7.8
Mean Differences
without
500-Hz Tone 63 -4.6 +2.5 +2.4 +0.5 +5.4 -1.8 +5.9 +7.8
B-20
-------
Table B-12
Fishken (First Experimental Series)
Effect of Tone-to-Noise Ratio on Standard Deviations (in Decibels)
Frequency Weighting Calculation Procedure
A Dl D2 E VI VII PNL ZWI
N
SDs Scharf,
et-^1-,1977,
("Corrected) 84 2.7 3.9 3.9 3.6 2.9 2.8 3.8 2.5
Table II
SDs
T/N ratios of
-5and+5dB 56 2.0 2.9 2.8 2.6 2.3 2.0 3.0 1.9
SDs
T/N ratios of
+ 15 dB 28 2.0 5.5 5.5 4.4 3.7 4.0 5.2 4.0
B-21
-------
Table B-13
Fishken (First Experimental Series)
Effect of Tone-to-Noise Ratio on Mean Differences
(Calculated Minus Observed Loudness Levels, in Decibels)
Frequency Weighting Calculation Procedure
A Dl D2 E VI VII PNL ZWI
N
Mean Diffs.
Scharf, et.al.,
1977. Table IV 84 -4.8 +2.1 +2.0 +0.3 +4.9 -1.9 +5.5 +7.8
Mean Diffs.
T/N Ratios of
-5 and +5 dB 56 -6.0 +1.3 +1.1 -0.9 +4.0 -2.5 +4.7 +7.8
Mean Diffs.
T/N ratio of
+15 dB 28 -2.1 +3.9 +3.9 +2.5 +6.5 -0.80 +6.9 +7.7
B-22
-------
The overall SDs are reduced by about 1.0 dB by omitting those stimuli
that produce tone-to-noise ratios of +15 dB. A tone-to-noise ratio of +15 dB
inflates the SDs for all descriptors exceot the A-weighting.
In contrast to the data for annoyance, Table B-13 shows that a tone-to-
noise ratio of +15 dB produces an overestimation of perceived loudness level
(not an underestimation). Only Zwicker's procedure does not overestimate at
+15 dB more than at lower tone-to-noise ratios.
c) Overall Sound Pressure Level of Tone and Noise Complex
A striking reduction in standard deviations is obtained by omitting those
data for noises at 30 and 40 dB sound pressure level. With the exception of
Mark VII and Zwicker's procedure, none of the weighting or calculation proce-
dures was designed to assess loudness below 40 dB sound pressure level. There-
fore, the use of these procedures for calculating the loudness of noises at
low sound pressure levels is not entirely justified.
Table B-14 gives the mean SDs calculated on the basis of sounds at all
sound pressure levels from 30 to 90 dB (from Table IV of Scharf, et. al.,
1977) and on the basis of only those sounds between 50 and 90 dB. The SDs
for the four frequency weightings go down dramatically from an average of
2.5 dB to 0.21 dB. The SDs for the four calculation procedures go down from
2.0 dB to 0.9 dB. Variability also went down quite a bit for Fishken's
second experimental series when the two lowest levels were ommitted.
The overall sound pressure level of the tone and noise complex also
modifies the difference between predicted and measured loudness levels.
Table B-15 provides an example from the second series of measurements by
Fishken for a constant tone-to-noise ratio of +15 dB. The discrepancy
B-23
-------
Table B-14
Fishken: Standard Deviations (in Decibels) with and without
Low Sound Pressure Levels. First Experimental Series
Frequency Weighting Calculation Procedure
A Dl D2 E VI VII PNL ZWI
N
Mean SDs from
Scharf, £t/_aJL- ,
1977 Table IV 84 2.5 2.5 2.5 2.5 2.0 3.3 1.1 1.4
(30 to 90 dB SPI)
SD Means with-
out 30 and 40
dB overall 60 .21 .21 .20 .21 1.1 1.2 0.35 1.0
sound pressure
level
B-24
-------
Table B-15
Mean Differences (in Decibels) from Fishken's Second
Experimental Series as a Function of Loudness Level
(Tone-to-Noise Ratio +15 dB)
Frequency Weighting Calculation Procedure
A Dl D2 E VI VII* PNL ZWI
OASPL
90 +0.5 +7.0 +7.2 +3.4 +7.4 -0.8 +10.4 +8.0
80 -0.9 +5.5 +5.6 +2.0 +5.9 -2.3 +9.1 +8.1
70 -2.0 +4.4 +4.5 +0.9 +5.5 -3.0 +8.0 +8.0
60 -0.3 +6.0 +6.1 +2.6 +8.2 -0.4 +9.5 +10.1
50 +2.2 +8.5 +8.6 +5.2 +11.1 +3.1 +11.6 +12.1
40 +5.5 +11.8 +11.9 +8.4 +14.0 +6.5 +14.1 +14.2
30 +10.3 +16.6 +16.7 +13.2 +17.7 +9.6 +17.8 +17.0
*Note that Mark VII are unadjusted values.
B-25
-------
between predicted and measured loudness levels decreases somewhat from 90
to 70 dB overall sound pressure level and then grows progressively larger
as sound pressure level becomes smaller.
B-26
-------
APPENDIX C
STEVENS'S TONE CORRECTION - 1970 PRELIMINARY PROPOSAL
Stevens's tone correction may be added to any of the descriptors examined
in this report. However, the spectrum must be smoothed; that is, the tonal
component or components removed, before the descriptor is calculated for the
noise. Then the tone correction in decibels calculated according to Stevens's
procedure is added to the descriptor's value. Since the correction worked
poorly when used with Mark VII for which it was intended, it is not surprising
that it fares no better with the seven other descriptors as shown in Tables C-l
and C-2 for SDs, and in Table C-3 for mean differences.
Table C-l
Standard Deviations (in Decibels) for 314 Spectra from
13 Studies with Tonal Components Listed in Column 1, Table VI.
(SDs are Given for Each Descriptor with and without a Correction,
Based on Preliminary Tonal-Correction Procedure of S.S. Stevens,
Added to the Raw Descriptor Value. Means were not Weighted
According to the Number of Contributing Values.)
Frequency Weighting Calculation Procedure
A Dl D2 E VI VII PNL ZWI
Mean SD
Uncorrected
Corrected
SD of SDs
Uncorrected
Corrected
2.6 2.4 2.4 2.3 2.1 2.1 2.4 2.3
3.3 3.0 3.1 3.0 3.0 3.0 3.0 3.0
1.4 1.2 1.3 1.2 1.0 1.1 1.2 1.4
1.8 1.4 1.5 1.4 1.4 1.4 1.4 1.4
C-l
-------
Table C-2
Standard Deviations (in Decibels) for 260 Spectra from 6 studies with
and without Tonal Components Listed in Column 1, Table VII.
(SDs are Given for Each Descriptor with and without a Correction
Based on Preliminary Tonal-Correction Procedure of S.S. Stevens,
Added to the Raw Descriptor Value. Means were not Weighted
According to the Number of Contributing Values.)
(Attribute Judged: Annoyance, Unacceptability, etc.)
Frequency Weighting Calculation Procedure
A Dl D2 E VI VII PNL ZWI
Mean SD
Uncorrected 2.5 2.0 2.1 1.9 1.9 1.9 2.1 2.8
Corrected 2.7 2.3 2.4 2.3 2.1 2.2 2.4 2.6
SD of SDs
Uncorrected 1.2 0.8 0.9 0.8 0.8 0.9 0.9 1.5
Corrected 1.4 1.1 1.2 1.1 1.0 1.1 1.3 1.5
C-2
-------
Table C-3
Mean Differences (in Decibels) (Calculated Minus Observed Levels)
Differences are Given for Levels Calculated Without and With
a Tonal Correction Proposed on a Preliminary Basis by
S.S. Stevens. Based Upon 141 Spectra from 6 Studies with
Tonal Components Listed in Table XII, Column 1
Frequency weightings
A Dl D2 E VI VII PNL ZWI
Mean of Mean
Differences
Uncorrected -7.7 -1.0 -1.5 -2.9 2.9 -4.6 4.1 7.1
Corrected -5.6 1.6 1.3 -0.2 5.9 -1.3 6.9 10.7
SD of Means
Uncorrected 4.7 4.9 5.0 4.6 4.0 4.0 4.8 3.3
Corrected 6.6 7.4 7.6 7.2 7.0 6.9 6.9 6.6
C-3
-------
APPENDIX D
ERRATA AND ADDENDA TO SCHARF, ET. AL. (1977)
1. Errata
Several computational errors were noted in four Tables shown in Scharf,
et. al. (1977). Although these corrections do not change the overall inter-
pretation of results in that report, the revised Tables are included herein.
Table D-l (Corrected Table II of Scharf, et. al.): A computational
error was noted in line 3 based on some of Fishken's data. This correction
produced a small change in the mean SDs and in the SD of SDs across the 11
descriptors.
Table D-2 (Corrected Table IV): Computational errors were noted in
line 1, based on the Berglund, et. al. data, in line 2, based on some of
Fishken's data, and in line 8, based on the data by Molino. These correc-
tions produced small changes in the calculation of the mean of the mean
differences and in the SD of the means for the C- and D-weightings and for
Mark VII, PNL, and PNLC.
Table D-3 (Corrected Table V): The computational changes made in
Table D-l resulted in small changes in the values of the SDs in lines 1, 7,
9, and 13.
Table D-4 (Corrected Table VI): The computational changes made in
Table D-2 resulted in small corrections to the values of mean differences
in lines 1 and 9.
2. Addenda
A repeated-measures analysis of variance (ANOVA), treating studies like
subjects, was performed on the data in Table II of Scharf, et. al. (1977)
D-l
-------
Table D-l. Variability of Calculated Levels of Noise by Study
(Standard Deviations in Decibels Computed Either from the Calculated Levels of a
Group of Sounds Judged Subjectively Equal or from the Differences Between Calculated
and Judged Levels. The Smaller the Standard Deviation, the Closer the Scheme Comes
to Predicting the Subjective Equality of a set of Sounds)
STUDY
Berglund ,
Borsky
Fisken
Jahn
Kryter
It'll-
Kryter and Pearsons
Lubcke, et. al .
Mo lino
Pearsons
Pearsons ,
Pearsons
Quietzsch
NUMBER
N/n OBSERVERS
18/3 30
13/13* 319
84/12* 12
21/3* 8
10/10 28
17/17* 4-100
i 9/9 13-19
11/11 12
20/20 12
30/5* 7
and Bennett 30/30 20
et. al.
and Wells
Rademacher
Robinson
Bowsher
Spiegel
and
Wells (aircraft)
Wells (unpubl.)
Wells 300
Wells 400
Wells UHV
Yaniv
20/20 20
103/54* 20
19/19* 20,20
27/27 20
10/10 20
24/24 20-25
10/5* 558
20/20 10
20/20 10
30/30 35
33/33* 30
42/42 30
60/60 30
25/25 31
11/11 10
11/11 10
11/11 10
Mean SD
Sd of SDs
LEGEND :
N
number of
pressure
conditions (e.g. different
levels, instructions,
A
4.6
3.6
2.7
4 . 5
1.3
2.4
3.5
2.0
2.3
4.4
4.3
1.7
6.5
2.8
4.2
3.8
2.2
1.9
4.7
5.3
1.6
1.1
3.7
2.5
1.5
1.6
2.0
2.6
3.05
1.4
sound
I
4,
3.
2.
4
1.
5,
4.
2
2.
4
4
4
5
3
4
6
2
2.
6.
4.
2.
1.
5,
4,
0
2
1
1
3,
1,
i
.6
.0
.9
. 6
.3
.3
.8
.2
.1
.6
.5
.0
.1
.4
.4
.3
.6
.8
.2
.9
.4
.7
.2
.2
.9
.2
.7
.2
.55
,6
4
2
3
4
1
6
5
2
2
5
4
4
5
3
5
7
3
3
6
5
3
2
6
4
1
4
3
2
4
1
C
.6
.8
.0
. 6
.4
.5
.4
.3
.2
.6
.7
.8
.3
.6
.7
.0
.2
.1
.8
.1
.5
.1
.6
.9
.4
.2
.4
.8
.16
.6
Dl
4.6
3.3
3.9
1.2
3.4
2.8
1.6
2.6
2.9
3.5
1.4
2.5
1.8
4
3
3
1
2
3
1
2
2
3
1
2
1
4.0 4
3.3
1.8
1.4
4.2
3.5
1.2
1.3
2.4
2.5
1.3
2.2
2.4
2.9
2
2
1
4
4
1
1
2
2
1
2
2
3
2.65 2
1.1 1
Mark
D2
.6
.5
.9
.3
.6
.1
.7
.8
.9
.7
.4
.8
.8
.3
.9
.0
.5
.0
.1
.3
.3
.7
.0
.5
.3
.7
.3
.73
.1
VI
MARK
E VI VII PNL PNLC ZWI
4.6 3.8 3.9 5.6 5.6 3.7
3.3 3.0 3.0 3.8 4.2 3.4
3.6 2.9 2.8 3.8 3.6 2.5
1.2 0.9 0.9 1.0 1.5 0.8
3.7 2.5 2.9 2.8 2.6 1.7
2.8 2.1 1.9 2.1 2.2 3.7
1.5 2.5 1.8 1.8 1.4 1.5
2.6 2.1 2.0 2.2 2.3 1.6
2.9 2.4 1.8 2.5 2.6 2.6
3.3 2.8 2.8 2.9 2.2 3.7
1.7 1.3 1.5 1.3 1.3 1.8
3.0 2.2 2.2 3.0 2.6 2.1
1.9 2.4 2.3 2.5 2.7 2.6
4.2 3.1 3.2 4.0 4.2 3.3
3.8 2.5 2.5 2.6 2.8 2.5
1.9 1.6 1.7 1.6 1.7 1.6
1.9 1.2 1.6 1.1 1.4 0.9
4.2 2.4 1.9 3.2 3.7 2.4
3.6 2.6 2.6 2.9 3.2 3.0
0.9 1.2 1.2 1.3 1.7 2.2
1.1 0.9 0.9 1.2 1.6 1.1
2.1 2.1 2.2 2.3 2.4 5.3
2.6 2.5 2.6 2.5 1.8 3.1
1.3 1.1 1.0 1.3 1.4 0.9
1.6 2.6 4.6 4.9 2.0
1.7 2.7 1.5 2.7 3.2 0.9
2.1 1.7 1.4 2.7 3.1 1.4
2.63 2.26 2.22 2.60 2.69 2.36
1.1 0.8 1.0 1.1 1.1 1.1
= ANSI S 3.4 (R1972) procedure for the
computation of noise
tone-to-noise ratios)
n
*
number of
standard
different spectra
deviation based on average
of
two or more distinct sets of measurements
A,B,C
Dl
D2
E
standard
sound-level meter weightings
meter weighting adopted by IEC
weighting
weighting
Mark
PNL
PNLC
ZWI
VII
values suggested by K. Kryter
values proposed for trial
and
= based on modification of Mark VI
(S. S. Stevens, JASA, 1972, 51
= perceived noise level
= PNL with tone correction as per FAR 36
= based on Zwicker's loudness calculation
system. Program from E. Paulus and E.
Zwicker, Acustica, 1972, 27. Free-fie
(FF) and diffuse-field (DF) values use.
as appropriate. For earphone listenini
study by ANSI
FF values used.
D-2
-------
Table D-2
MEAN DIFFERENCES (in decibels) (CALCULATED MINUS OBSERVED LEVELS)
o
STUDY
Berglund, et al .
Fishken
Jahn
Kryter and Pearsons
Lubcke, et al
Mo lino
Quietzsch
Raderaacher
Spiegel
Yaniv
N/n
18/3*
84/12*
21/3*
10/10
9/9
11/11
20/20
30/5*
27/27
10/10
24/24
20/20
20/20
11/11
11/11
11/11
See Legend for
A B
-12.9
-4.8
-1.0
-11.9
-8.9
-18.8
-17.3
-6.5
-14.6
-13.0
-8.8
-12.8
-11.9
-7.3
-10.3
-11.8
-4.7
-5.1
-1.7
-10.8
-7.6
-16.9
-15.7
-4.8
-13.0
-9.4
-4.2
-10.9
-10.0
-3.9
-6.9
-8.4
Table II.
C Dl
0.4
-5.1
-1.7
-10.3
-7.0
-16.0
-14.9
-3.1
-11.6
-7.8
-2.4
-10.0
-9.0
-1.3
-4.3
-5.8
-4.1
2.1
5.8
-5.1
-2.3
-13.0
-11.7
-0.8
-8.3
-6.9
-2.1
-6.7
-5.8
-1.7
-4.7
-6.2
D2
-6.7
2.0
6.0
-5.3
-2.2
-13.3
-11.8
-1.0
-8.6
-7.5
-3.0
-7.0
-6.2
-2.4
-5.4
-6.8
E
-6.3
0.3
2.9
-7.7
-3.7
-14.8
-13.3
-2.4
-10.3
-7.9
-3.7
-7.6
-6.8
-3.6
-6.6
-8.1
MARK
VI VII
2.5
4.9
8.8
-0.3
0.3
-8.6
-6.2
6.4
-3.5
-1.4
1.7
-1.5
-2.8
-
0.2
0.9
-6.0
-1.9
1.3
-7.8
-7.3
-13.3
-14.0
-1.0
-11.0
-7.6
-5.3
-9.4
-10.9
-4.3
-4.9
-6.3
PNL
1.9
5.5
9.9
1.1
2.1
-9.4
-5.2
5.1
-2.5
-2.9
3.9
-3.9
-2.3
-1.5
-0.9
-0.9
PNLC
2.6
10.7
15.6
2.3
5.3
-8.2
-3.7
6.3
0.5
-1.0
6.3
-1.8
1.0
-0.1
0.5
0.4
ZWI
8.6
7.8
11.2
5.1
4.1
-2.4
-0.7
12.3
1.8
4.7
8.0
1.0
0.7
6.3
6.5
6.2
Mean of Mean diffs.
SD of Means
-10.8 -8.4
4.53 4.36
-6.9 -4.5 -5.0
4.85 4.74 4.84
-6.2 -0.13 -6.9 -0.0 2.3 5.1
4.55 4.54 4.27 4.71 5.66 4.16
-------
Table D-3
EFFECT ON STANDARD DEVIATION OF FOUR PARAMETERS (Standard Deviations in Decibels)
U
-P-
See Legend for Table II.
No. of
VARIABLE
1. Attribute Judged
Loudness
Acceptabil ity
2. Type of Noise
Aircraft
Industrial
Vehicle
Household
Art if icial
i; iscel .
3. Tonal Components
Present
Absent
STUDIES/
SDs
9/15
10/12
7/8
3/4
1/1
1/3
7/10
3/4
9/12
10/15
A
3.2
2.9
2.0
2.7
2.2
2.1
4.1
3.5
3.0
3.2
B
3.5
3.7
3.0
2.7
2.6
1.8
4.6
4.1
3.5
3.7
C
4.1
4.3
3.5
2.8
3.2
3.5
5.0
4.9
3.9
4.5
Dl
3.0
2.3
1.9
2.7
1.8
2.5
3.2
2.9
2.5
2.9
D2
3.1
2.3
1.8
2.8
2.0
2.8
3.3
2.9
2.5
3.0
E
2.9
2.3
2.0
2.7
1.9
1.8
3.2
3.1
2.4
2.9
VI
2.5*
2.0
1.5
2.5
1.6
2.2*
2.6
2.3
2.2
2.4*
VII
2.4
2.0
1.6
2.4
1.7
1.8
2.7
2.1
2.3
2.2
PNL
3.0
2.3
1.9
2.9
1.6
3.3
2.9
2.6
2.4
2.8
PNLC
3.2
2.2
2.0
1.7
1.7
3.7
2.8
2.8
2.4
3.0
ZWI
2.2
2.6
1.6
2.1
1.6
1.4
3.2
2.3
2.7
2.2
4. Mode of Sound Presentation
free Field
Diffuse Field
Earphones
11/14
7/8
3/6
2.7
3.7
3.0
3.1
4.7
2.9
3.7
5.3
3.8
2.1
3.1
3.4
2.2
3.1
3.5
2.1
3.3
3.0
1.9
2.3
3.1*
1.9
2.3
2.9
2.1
2.6
3.8
2.1
2.8
4.0
2.3
2.5
2.4
* 1 SD less
-------
Table D-4
EFFECT ON MEAN DIFFERENCES OF TWO PARAMETERS (Calculated minus observed levels in decibels )
o
Ol
See Legend for
VARIABLE
1. Type of Noise
Aircraft
Industrial
Vehicle
Household
Art if ic ial
Miscel .
2. Mode of Stimulus
Free Field
Diffuse Field
Earphones
Table II.
No. of
STUDIES/
MEANS
1/1
3/4
1/1
1/3
3/5
2/3
Presentat
4/5
4/5
3/6
A
-12.8
-15.0
-8.8
-9.8
-7.9
-11.9
ion
-14.3
-10.6
-8.0
B
-10.
-11.
-4.
-6.
-7.
-9.
-12.
-8.
-5.
2
6
2
4
1
1
1
5
1
C
-8.7
-9.6
-2.4
-3.8
-6.6
-7.5
-11.0
-7.4
-3.0
Dl
-5.1
-8.4
-2.1
-4.2
-1.4
-5.3
-8.0
-4.5
-1.5
D2
-5.5
-9.4
-3.0
-4.9
-1.5
-5.7
-8.4
-4.8
-2.2
E
-7.
-10.
-3.
-6.
-3.
-6.
-10.
-5.
-3.
3
5
7
1
0
9
0
7
6
VI
0.9
-3.1
1.7
-0 . 6**
1.9
0.5
-3.4
0.2
3.5
VII
-6.6
-10.2
-5.3
-5.2
-5.6
-6.5
-10.3
-7.2
-3.7
PNL
1.4
-3.6
3.9
-1.1
2.3
-0.1
-2.4
-0.4
2.3
PNLC
_
-3.2
6.3
0,3
5.8
2.0
-0.6
2.0
5.0
ZWI
6.1
2.7
8.0
6.3
9,5
6.3
2.4
4.6
7.8
** 2 means
-------
(after being corrected as explained above). Table II gave the SDs for 28 sets
of spectra for eleven descriptors (six sound-level meter frequency weightings
and five calculation procedures). The results of the ANOVA are given in Table
D-5. Although the differences among the mean SDs for the eleven descriptors
were small, they were highly significant, as were the differences among studies
and subsets. However; the interaction between procedure (descriptor) and study
was not significant.
To determine which mean SDs differed from each other significantly, a
Duncan's multiple-range test (Lynch and Huntsberger, 1976) was performed on
the matrix of differences between descriptors given in Table D-6. The number
of asterisks indicates the level of significance. Generally, differences
greater than 0.45 dB were significantly different at the .05 level or better.
Thus the A-weighting had significantly larger SDs than four of the five calculation
procedures. With the exclusion of B- and C-, among the four frequency weight-
ings only A- and Dl-weightings differed significantly. Except for PNLC, none
of the calculation procedures differed significantly from one another. (N.B.
Table D-6 supercedes Table VII in Scharf, et. al. (1977). Table VII was based
on t-tests and was presented as a preliminary analysis pending an ANOVA and a
more appropriate multiple-range test.
D-6
-------
Table D-5
REPEATED MEASURES ANOVA
(Based on 28 standard deviations from 20 studies.)
Source Variance
Weighting or calculation
procedure
Study
Procedure x Study
Total
Sum
of Squares
95.28
274.04
150.56
530.14
Degrees
of Freedom
10
27
270
307
Mean
9.53
10.14
.56
F P
17.08 «.001
18.20 «.001
-------
Table D-6
DIFFERENCES ! IN DECIBELS BETWEEN MAN STANDARD DEVIATIONS IN TABLE II.
A
B
C
ni
D2
E
VI
a
00 VII
PNL
PNLC
B C Dl D2 E
.50* 1.11*** -.40* -.32 -.42
.61** -.90*** -.82** -.92***
-1.5.*** -1.43*** -1.53***
.03 -.02
Results of Duncan's Multiple Range Test -.10
N=28
blank = Not Significant
* = Significant at .05 or better
** = Significant at .01
*** = significant at .001
-'•Standard deviation for a given calculation schem ie listed in
for the calculation scheme, with which it is paired, listed
Legend :
A, B, C
Dl
D2
E
Mark VI
standard sound-level meter weightings
meter weighting adopted by IEC
weighting values suggested by K Krj'ter
weighting values proposed for trial and
study by ANSI
ANSI S3. 4 (R1972) procedure for the
VI VII PNL PNLC
-.79*** -.83*** -.45* -.36
-1.99*** -1 33*** -.95*** -.gg***
-1.90"** -1.94*** -1.56*** -1.47***
-.39 -.43 -.05 .04
-.47* -.51* -.13 -.04
-.37 -.41 -.03 .06
-.04 .34 .43
.38 .47*
.09
the column of this matrix is subtracted from
in the row. Thus B minus A =.50S Dl minus A
Mark VII based on modification of Mark VI
JASA, 1972, 51)
ZWI
-.69
-1 . 19***
-1.80***
-.29
-.37
-.27
.10
.14
-.24
-.33
the deviation
=-.40, etc.
(S.S. Stevens,
PNL perceived noise level
PNLC PNL with tone correction as per FAR 36
ZWI based on Zwicker's loudness calculation system.
Program from E. Paulus and E. Zwicker, Acustica,
computation of the loudness of noise
1972, 27. Free-field (FF) and diffuse-field (DF)
values used as appropriate
-------
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R-l
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R-2
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
REPORT NO.
EPA 550/Q-7q-in?
3. RECIPIENT'S ACCESSION NO.
TITLE AND SUBTITLE
Part II: Comparison of Various Methods for Predicting
the Loudness and Effects of Spectral Pattern Accept-
ability of Noise and Tonal Components
5. REPORT DATE
Mov 1979
6. PERFORMING ORGANIZATION CODE
AUTHOR(S)
B. Scharf and R. Hellman
8. PERFORMING ORGANIZATION REPORT NO.
PERFORMING ORGANIZATION NAME AND ADDRESS
Auditory Perception Laboratory
Northeastern University
Boston, Massachusetts 02115
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
2. SPONSORING AGENCY NAME AND ADDRESS
U.S. Environmental Protection Agency
Office of Noise Abatement and Control
Washington, D.C. 20460
13. TYPE OF REPORT AND PERIOD COVERED
(ANR-471)
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
16. ABSTRACT
The present report is a continuation of an earlier report by Scharf, Hellman
and Bauer (1977). The objectives are (1) to determine whether subjective judgments
of particular types of noise, categorized by spectral shape, are better approxi-
mated by some descriptors (frequency weightings and calculation procedures) than
by others, and (2) to investigate the role of tonal components in these studies and
to assess the adequacy of several tone-correction procedures. The analysis of data
by spectral shape produced a mixed outcome. Results showed that no overall advan-
tage would accrue from regrouping sets of data across studies on the basis of similar
spectral shapes. However, although variability was not reduced when considered acros
nine spectral categories, the interaction between spectral shape and descriptor was
highly significant (p < .001). The examination of over 500 spectra with and without
tonal components provided only tentative support for the trends noted in the litera-
ture. When the judged attribute is either loudness or noisiness, tonal components
do not seem to add to the subjective magnitude of broad-band noise below 80 dB sound
pressure level. At higher levels, according to one large-scale study, tonal compon-
ents seemed to add the equivalent of 2 dB to the judged noisiness. No data could be
located that would permit adequate assessment of the contribution of tonal components
to the "absolute" magnitude (continued on page 2, attached)
\
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.IDENTIFIERS/OPEN ENDED TERMS
COSATl Field/Group
Loudness, Spectral Patterns, Tonal
Components, Calculation Procedures,
Frequency Weightings
18. DISTRIBUTION STATEMENT
Available at EPA/ONAC and
gle Park, North Carolina
Research Trian-
19. SECURITY CLASS (ThisReport)
Unclassified
20. SECURITY CLASS (This page)
Unclassified
22. PRICE
EPA Form 2220-1 (9-73)
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- 2 -
...of judged annoyance or unacceptability (as distinct from noisiness or loudness).
Given the small effect of tonal components in the present group of studies, the
evaluation of three different tone-correction procedures (FAR 36, 1969; Kryter and
Pearson's, 1965; and Steven's, 1970) could not lead to definitive conclusions about
their relative merits. Although a small correction may be necessary for the pre-
sence of tonal components at high levels, the tone-correction procedures now avail-
able cannot be properly evaluated until more appropriate data that demonstrate the
need for a tone correction are obtained.
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