INDIVIDUAL SUBJECTIVE PREFERENCE OF LISTENERS TO VOCAL MUSIC SOURCES IN RELATION TO THE SUBSEQUENT REVERBERATION TIME OF SOUND FIELDS
H.
Graduate
and
H. SETOGUCHI
Kirishima International Concert Hall,
The
purpose of this study is to evaluate individual differences and intraindividual changes of subjective preference of
simulated sound field judged by listeners in changing subsequent reverberation
time Ts„b using a vocal source. A great deal of effort has been made studying
subjective preferences by using music or speech. Subjective preference tests
were conducted by changing Ts„b, which is one of the four orthogonal-objective
parameters of sound field.
1. INTRODUCTION
It is well known
that subjective preference evaluation of sound fields is accompanied by individual
differences [1, 2]. Using results from subjective preference tests in relation
to. orthogonal parameters of sound fields, each
listener can select his or her optimum seat in a given concert hall [3].
Psychological evaluations in relation to preference of sound fields have been
considered by their global results as an average of many subjects and also for
each subject [4, 5]. In order to clarify individual differences in subjective
preference, intra-individual changes should be investigated. The variations of
preference evaluations caused by aging, seasons, time (morning, evening or
night), a certain period of time during the repetition of psychological tests,
and so on, are considered. As a typical example, a person's hearing level may
be affected by aging. In this study, the variation of preference evaluations
during the repetition of psychological tests is applied to intra-individual
changes.
In a previous study on intra-individual changes in
SPL by using a music source [6], it was found that subjects with large
a values (see later for the definition of a) have smaller intra-individual
changes than subjects with small ones, and the range of the variation of
preferable SPL is small.
Subjective
preference evaluations for intra-individual changes are identified by two
factors from subjective preference curves obtained from paired-comparison tests
as well as their global case and individual differences. One factor is the
value at the most preferred parameter, which coincides with the peak of the
preference curves. The other is the sharpness of the curve, a, which is an
index of the degree of preference; see equation (3). For a unit variation of a
parameter, the scale value for a certain subject with a large a value changes
more rapidly than that of other subjects with a small a. Procedures for
obtaining these parameters are described in the next section.
For
vocal music, which is one of the main components of performances in opera
houses, this study evaluates listener's individual differences and
intra-individual changes in subjective preference to various simulated sound
fields. Subjective preference tests were conducted by changing subsequent reverberation
time, TS„b, which is one of the four orthogonal parameters that describe
subjective preference to sound fields. The value of
TS„b is defined by the decay rate of the
sound pressure level after arrival of the first reflection until -60 dB.
For calculating scale values of tests, a simple method of calculating
individual subjective preference was adopted [7].
2. EXPERIMENTAL METHOD
2.1. CHARACTERISTICS OF A
SOUND SOURCE
The
sound source used was an initial 6-0 s piece of a solo performance of a soprano
single ("O mio babbino
caro" from "Gianni Schicchi"
composed by G. Puccini) recorded in an anechoic chamber. Values of ce, which is the effective duration of the normalized
autocorrelation function (ACF), O(i), of a short-time
moving ACF or running ACF (2T = 2-0 s with the interval of 100 ms) [8] for the initial 6-0 s
part of the source reproduced in the listening semi-anechoic chamber, were
calculated. The waveform and values of running r'. are indicated in Figures 1(a) and (b) respectively. The
short-time moving ACF was calculated in order to obtain the
minimum of its running ie, which represents the most rapid
movement of music, activating the left cerebral hemisphere [9]. As indicated in
Figure 1(c), the running ie is practically obtained by calculating
the decay rate extrapolated in the range from 0 dB, at the origin, to - 5 dB.
The 2-0 s duration corresponds to the psychological present [10] and the
minimum duration of signals corresponds to response to any subjective
attributes. The most preferred Ts„b averaged for a number of listeners can be
calculated by using the equation [11]
[Tsub] p =23(ôe)min.
where (ôe)min
is the minimum value of
ôe for the source music. The calculation
of global preferable subsequent reverberation time [Ts„b] p is about 0-53 s, which is shorter than usual music sources
but longer than that of speech signals.

2.2. PSYCHOLOGICAL EXPERIMENT
Paired-comparison tests were conducted in a semi-anechoic room (see Figure 2). With [Ts„b] p taken to be about 0-53s as mentioned above, the subsequent reverberation time Ts„b of the sound field was changed from 0-1 to 1-6 s (see Table 1). The conditions of the other orthogonal parameters were fixed as indicated in Table 1. The initial time-delay gap between the direct sound and the first reflection, At,, was fixed at 14 ms near to the most preferred value [Atl] p (1 - log 10A) (Te)min -_ 16 ms. The IACC is near to unity because the two loudspeakers were set in front of the subjects. The total amplitude of reflections A is kept constant at 2-0. The duration of each stimulus presented to subjects was 6-0 s. The time interval between the two stimuli in a pair was 1-0 s and between each pair lasted 4-0 s.
Figure 2.
Experimental
set-up of subjective preference tests controlling both the initial time delay
gap between the direct sound and the first reflection, dtl, and the subsequent reverberation time, Tsdb.

There are 10
2.3. CALCULATION OF THE SCALE
VALUE
We
used the subjective responses from each subject to calculate the scale values
of preference for each sound field. The procedure for calculating scale values
of preference is outlined in Table 2. The scores for each presented pair are
obtained by giving scores of + 1 and 0 corresponding to positive and negative
judgments
where
/ Si-Sj / Poor = Sj-Si >0 , if Yi=0, =0 if Yi=0


The value of
ë
corresponds to the average error of
the scale value. This should be small enough: for example, less than 10%. The
value of Yi represents the score for each alternative judgment.
Another observation is that, when the poorness number is K, satisfying the condition expressed by upper part of equation (6), then the percentage of violations d is defined by
d= 2K/ N(N-1) x 100
3. RESULTS
3.1. INDIVIDUAL DIFFERENCES AND GLOBAL CASE
The measured results of the scale values of preference as the function of the Tsub for each subject and its global case are indicated in Figure 3. In this figure, different symbols represent the results from each subject, and the bold line represents the averaged value as the global result.

As the sharpness of the curves are found
to be different for each side of the preference curves' peaks, two values of a
for both sides of the peak are considered as as for
Tub < [ Tub] p, m and al for
Tsub >
[Tsub]
p,m
in equation (3). The range of most preferred values of subsequent reverberation
time [Tsub]p,m obtained for all subjects in the tests was
between 0-55 and 122 s. The largest value of as was 2-02 (subject B) and the
smallest one was 0-97 (subject F). On the other hand, the largest value of a,
was 1104 (subject G) and the smallest one was 1-69 (subject C). The values of
a, are always greater than those of as, for all subjects tested without exception.
The experimental measurements of [Tsub ] p,m, as, and al for each
subject as well as global results are listed in Table 3. The goodness of fit of
this model for each subject, expressed using A, in equation (5) representing
the poorness of the model for each subject, gives zero except for 0-04 for
subject B. The values of din equation (7) were also zero for all subjects
except for 0- 1 for subject B. These small values indicate that a consistent
model is achieved for this test. Individual difference is found in log([Tsub]p,m /
[Tsub]p) (p < 0-05) and as (p < 0-01) by use of
analysis of variance (ANOVA), as shown in Table 4. The method of ANOVA is
referred to in Appendix II. For example, subject B (as = 2-02 and a, =
7-09)
and subject G (as = 1-87 and a, =
1104)
show a sharper preference curve than subject D (as = 1-38 and al = 327) and
subject F (as = 0-97 and al = 2-12). In the global results obtained in the
tests, [Tsub]p,m was -0.78 s, and values of
as and al were 1-53, and 524 respectively. This means that for
Tsub greater than the most preferred value,
preference curves are sharper than those for Tsub
less than the most preferred value.

Figure 4.
3.2. INTRA-INDIVIDUAL CHANGES
The
measured results of intra-individual changes of subjective preference for each
subject (A-H) are indicated in Figure 4. In this figure, different symbols
represent the results in every four series of tests performed over three or
four days. Each peak value of the preference curves is shifted to the origin
without losing any information, because a scale value is a relative and a
linear scale. For example,

Figure 5.
There are only two curves of both subjects C and H, because
the other three sets could not be obtained. The measured results of log([Tsub]p,m /
[Tsub]p),
as, and cc, for each set are indicated in Figure 5. Subjects with large a
values, like subjects B and G, have small intra-individual changes with respect
to values of log([Tsub]p,m1
/ [Tsub1p),ás.
Standard
deviations of these factors obtained from each set of tests are listed in Table
5. The values of subjects C and H, with only two sets, are not listed. Subject
B (0033) and subject G (0035) have the two smallest standard deviations of all
subjects, and subject D (0163) and subject F (0-168) have larger standard deviations. In relation to those of
ás
and ál, subject B (ás: 0-16;
ál: 1-84) and subject G
(ás: 026;
ál: 1-68) have smaller standard deviations
as well as the values of log([Tsub]p,m/[Tsub]p). On the other hand, subject D (ás:
0-61; ál: 321) and subject F (ás:
0-55; ál: 3-67) have larger standard deviations.
4. DISCUSSION
Values of both as and al of subjects B and G were greater than those of
the other subjects and have almost the constant values, and these values of
subjects D and
TABLE 5
The results of log([Tsub]p,m
l
[Tsub]p),
the values of as,
and oc, in every four series for each subject are
indicated in Figure 4. On both sides of the peaks, for subjects who have larger
a, such as subjects B and G, the standard deviations of log([Tsub]p,m/[Tsub1p)
for each set are small. On the other hand, for subjects who have smaller a,
such as subjects D and F, the preferable
Tsub values are larger:
0-163 and
0-168 respectively.
Relationship
between the standard deviations of log([Tsub]
p,m/[Tsub] p),
as and a, values for each subject
(except subjects C and H) are plotted in Figure 6. Subjects with large a
values, such as subject B or subject G, have smaller intra-individual changes,
so that the standard deviations of preferable
T,.b is small. On the other hand, subjects
with small a values such as subjects D and F show minor preferences as T,.b changed. This result is similar to
that of previous results for SPL [6].
The value of
[Tsub]p
calculated by using equation (1) with (ôe)min (= 23 ms) is 0-53 s. For the global subjects, the value of [Tsub]p,m obtained
by the tests was 0-78 s, longer than the calculated value.
5.
CONCLUSION
Subjects with large a values indicate smaller intra-individual changes, so the standard deviation of log([Tsub] p,m/[Tsub] p) is small. On the other hand, subjects with small a values without sharp curves show minor preference as Tsub changed. The averaged value of preferred Tsub for vocal sources was 0.78 s, which is greater than the value (0-53 s) calculated by equation (1). Individual differences are observed in values of log([Tsub]p.m/[Tsub]p) and ás but not in value of ál.
ACKNOWLEDGMENT
The
authors wish to thank Mrs. Mikiyo Setoguchi
as a soprano singer for her cooperation in recording source signals. This work
is supported by the Ministry of Education, Grant-in-Aid for Scientific Research
(C), 9838022, 1998.
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MOM, K. AKIYAMA and Y. ANDO 1998
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14. H.
APPENDIX A
For
calculating the scale values of preference, a simple method [7] was used as an
approximation for case V of Thurstone's law of
comparative judgment [13]. It must be noted that the estimated scale value
obtained by this method is smaller than the result estimated by the case V of Thurstone's law, though high correlation coefficient (r =
0-99) was found between the scale values obtained from both methods. The
results of two recent psychological tests [14], including this test with five
sound fields show that the correlation ratio becomes about 1-26. This ratio may
be mainly changed by the number of sound fields and individual differences.
APPENDIX B
In
this article, the one-way analysis of variance (ANOVA) is adopted in order to
evaluate individual differences in relation to the values of factors, log([Tsub]p,m1[Tsub]p), as and a, as shown in Table 4. Its definitions
and usage are briefly described here. By use of the ANOVA, significance tests
of individual differences are conducted for the each factor which is
categorized by each subject as levels.
At
first, two hypotheses are set as follows. As the null hypothesis, each group,
categorized by each subject, is considered to be sampled from one population.
In this hypothesis, an individual difference is reserved. As the alternative
hypothesis, each group is considered to be sampled from different populations.
In this case, the null hypothesis is rejected and alternative hypothesis is adopted.
Hence individual difference is accepted.
The
values of F-ratio, F, are given as ratios of between-individuals variance and
residual variance, calculated by the following equations:
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Here the values of SA and SE are given as a square-sum due to between-individuals variation and residual sum of squares respectively. The values of dfA and dfE are degrees of freedom of between-individuals variation and residual respectively. The F-ratio is a statistical value representing the difference among groups. If the null hypothesis is correct, the expected value of the F-ratio approaches unity, and the individual difference is reserved. If the F-ratio is greater than unity, it is considered that individual differences exists for the factor. Judgments of the tests are estimated by comparison between the F-ratio of samples and the Fp-ratio Fp. The value of Fp can be obtained from the well known F-distribution with dfA, dfE and a significant level as a probability, p. If the F-ratio is smaller than the Fp value, difference among subjects and judgement for significant difference are reserved. If the value of F is greater than that of Fp, difference among subjects can be obtained. In this case, the null hypothesis is rejected and the alternative hypothesis is adopted. The value of p that the F is greater than Fp, is obtained as an upper-sided probability of the F-distribution. Values of p smaller than 0-05 and 0-01 indicate significant differences of each factors among subjects with their probability of 5 and 1 %, respectively.