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Evaluation of Support in Singing
Evaluation of Support in Singing *A. Sonninen, †A.-M. Laukkanen, ‡K. Karma, and *P. Hurme Jyva¨skyla¨, Tampere, and Helsinki, Finland
Summary: This study searched for perceptual, acoustic, and physiological correlates of support in singing. Seven trained professional singers (four women and three men) sang repetitions of the syllable [pa:] at varying pitch and sound levels (1) habitually (with support) and (2) simulating singing without support. Estimate of subglottic pressure was obtained from oral pressure during [p]. Vocal fold vibration was registered with dual-channel electroglottography. Acoustic analyses were made on the recorded samples. All samples were also evaluated by the singers and other listeners, who were trained singers, singing students, and voice specialists without singing education (a total of 63 listeners). We rated both the overall voice quality and the amount of support. According to the results, it seemed impossible to observe any auditory differences between supported singing and good singing voice quality. The acoustic and physiological correlates of good voice quality in absolute values seem to be gender and task dependent, whereas the relative optimum seems to be reached at intermediate parameter values. Key Words: Self-perception—Acoustic and perceptual voice quality— Electroglottography—Subglottic (oral) pressure—Spectrum—Breathing— Singing technique.
is singing with support or without it. Thus, the word support is also used by evaluators when assessing the perceptual singing voice quality and the presumed physiological background of it. Support, then, is a sensation that both singers and listeners have,1,2 at least when the listeners have experience in singing. Many singers regard support as essential in singing. As the world-famous soprano Birgit Nilsson puts it, “If one forgets the support, it’s [voice] like a flower without roots; after a while it begins to fade.”3 This self-perception4 must somehow be described.5 Support is closely connected with respiration, which can be reflected in the expressions: “breath support” and “Atemstu¨tze.” Sometimes in English, singers use metaphors such as “lean” or “rest on the voice.” Singing pedagogy mainly operates with the sensations of the singer and the listener. Researchers of singing, in turn, are more interested in the physiological and acoustic variables. Nadoleczny6 found in his profound study that 40% of singers
INTRODUCTION Support (appoggio in Italian, appui in French, Stu¨tze in German, sto¨d in Swedish, and tuki in Finnish) is a concept widely used by classically trained operatic singers. It refers to a sensation singers have during singing. In addition, it is often claimed that a trained ear can immediately hear whether someone
Accepted for publication August 2, 2004. From the *Department of Communication, University of Jyva¨skyla¨, Jyva¨skyla¨, Finland; †Department of Speech Communication and Voice Research, University of Tampere, Tampere, Finland; ‡Sibelius Academy, Helsinki; Finland. Address correspondence and reprint requests to Professor Aatto Sonninen, MD, PhD, Gummeruksenk. 3 B 24, 40100 Jyva¨skyla¨, Finland. E-mail: [email protected] Journal of Voice, Vol. 19, No. 2, pp. 223–237 0892-1997/$30.00 쑕 2005 The Voice Foundation doi:10.1016/j.jvoice.2004.08.003
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(N ⫽ 92) used combined “costo-abdominal” breathing, and 25% mainly used “costal breathing” for supported singing. (These terms refer to the observable inspiratory movements of the chest and abdomen.) According to Nadoleczny, support is a sensation caused by muscle and pressure receptors during expiration. According to the radiological studies undertaken by Schilling,7 two main types of support can be distinguished: diaphragmatic support and thoracic support. Vennard8 defines support as well-controlled respiratory [subglottic] pressure. Recent research on support seems to be shifting in medias res from breathing to the acoustic, aerodynamic, and physiological phenomena of voice production. Sonninen et al9 studied physiological and acoustic differences between supported and unsupported singing in nine professional classically trained singers. According to the results, supported singing was characterized by a longer maximum phonation time, lower vertical position of the larynx, higher subglottic (oral) pressure, faster glottal closing speed, and especially in male singers, a greater difference between the first formant region and the fundamental. Griffin et al10 found higher SPL, higher average and peak airflow, and lower open quotient of the glottis in supported singing compared with unsupported singing. F4 was also lower in supported singing. Griffin et al also questioned the singers about their definition of support. All subjects associated support with management of breathing and described supported singing as having better tone quality and greater ease of management. The present investigation aimed to study the perception of support and its relationship to physiological and acoustic variables. Aims of the study This study aimed to find answers to the following questions: 1. Is it possible to distinguish between supported and unsupported voices by auditory impression? 2. Do trained singers and nonsingers differ in their perceptions of supported and unsupported singing? 3. How is self-perception of support (singer as subject) related to auditory evaluation of support in one’s own recorded voice (same singer as object)? Journal of Voice, Vol. 19, No. 2, 2005
4. What is the relationship between “supported voice” and “good voice”? 5. What acoustic and physiologic parameters, if any, correlate with good and/or supported voice? It is important to note the ontological dimensions of the object of the present study (questions 4 and 5). For clarity, supported singing refers to something that the singer does and senses, whereas supported voice refers to something that the listener perceives and that, therefore, has acoustic correlates. METHODS Subjects Four female and three male professional singers volunteered as subjects in this study (Table 1). The subjects represented various voice types. They were aged 25 to 84 years. (The oldest subject, Vilho Kekkonen, has been registered in the Guinness Book of Records 1991 and 1996 as the oldest tenor who has given a concert.) Tasks We recorded the subjects in a quiet room when singing in upright position. They produced syllable sequences [pa: pa: pa:] at two pitches above and below the register transition area (from this on: high/ low pitch), which is common for both men and women (about C4 and G4). The subjects were instructed to produce the syllables (1) for at least 5 seconds at a constant pitch and loudness and (2) with varying intensity (pp – ff – pp) and (3) with a melodic figure (Figure 1), first with support and then immediately without support. The presupposition was that professional singers can sing with and without support. Recordings The acoustic signals were recorded on a tape recorder (Revox, Regensdorf, Switzerland) with a 30-cm mouth-to-microphone distance. Electroglottographic (EGG) signals were obtained with a dualchannel electroglottograph11 and recorded with the acoustic signals on a Revox tape recorder. Intraoral air pressure (DC) signals were registered with a manometer and recorded with a Racal Thermionic
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TABLE 1. Sex, Age, Voice Class, Voice Range, and Training of the Subjects Case
Sex
Class
Age yrs
a yrs
b yrs
c lowest
d transition
e highest
ST RV MH HV VK mean F G H mean
F F F F F
Mezzo-soprano Lyric soprano Dramatic soprano Soprano Lyric soprano
25.0 26.0 64.0 39.0 36.0 38.0 52.0 64.0 84.0 66.7
18.0 21.0 17.0 18.0 18.0 18.4 21.0 21.0 20.0 20.7
6.0 4.0 30.0 6.0 22.0 13.6 10.0 15.0 15.0 13.3
D3 E3 A3 D3 G3 E3-F3 E2 A2 C3 G#2
C4 E4 F4 F4 E4 D#4 E4 F4 F4 F4
A#5 D6 A5 D6 C6 B5–C6 G4 A4 C5 A4
M M M
Baritone Baritone Tenor
a: Age when vocal education started; b: duration of vocal education; c: lowest pitch; d: first register transition (for the females, second for the males); e: highest pitch. yrs ⫽ years. F ⫽ female. M ⫽ male.
instrumentation recorder (Racal Instruments, Irvine, Calif). Pressure was calibrated into centimeters of water (cm H2O) with a u-tube manometer. Intraoral pressure provided an estimate of subglottic pressure.12 Listening evaluation Three groups of listeners (N ⫽ 63) attended the listening evaluation. Group A consisted of the singers. Group B consisted of two amateur singers and three voice researchers without singing training. One of the amateur singers evaluated the samples twice. Group C (N ⫽ 50) consisted of student singers from the Sibelius Academy (N ⫽ 32) and professional singers and singing pedagogues (N ⫽ 18). The test tape included 170 randomized samples, each of 5-second duration (subjects ⫽ 8; task type ⫽ 3: sustained phonation, variation of loudness, melodic figure; pitch ⫽ 2: low, high; singing type ⫽ 2: with support/without support; thus, the basic number of samples was 8 × 3 × 2 × 2 ⫽ 96. Additionally, to study the reliability of the listening
FIGURE 1. Melodic figure sung by the subjects.
evaluation, 12 randomly chosen samples were repeated two to four times, summing up 33 samples, at random intervals during the listening test, especially close to the end of the test. Furthermore, in the case of very long, over 10 seconds, syllable sequences produced at constant pitch and loudness, we presented the listeners with a 5-second sample from both the beginning and the end of the sequence, resulting in 41 more samples. Thus, the number of samples presented to the listeners was 170). Three listening tests were conducted: Groups A and B listened to the samples in the same conditions, in an ordinary low noise room in free field. The listening evaluation for Group C was arranged in free field in a large auditorium in Sibelius Academy. All listening tests were carried out about 2 months after the recording sessions. The reason for this delay was to obtain from the singers evaluations of their samples that were as objective as possible. The listeners had two tasks: to evaluate the amount of “support” and to evaluate the voice quality in the samples. Both variables were evaluated on a continuous visual-analogous scale (VAS) from no support to 100% of support and from very poor quality to very good quality (0% to 100%). No definitions of support or quality were given to the listeners. The listeners’ first auditory impression was the object of interest. Therefore, only a 5-second pause was given between the samples. The listeners were allowed a repetition of a sample if necessary. Journal of Voice, Vol. 19, No. 2, 2005
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However, repetitions were requested only a few times during the tests. The duration of the test was about 40 minutes. Analyses We made all physical analyses of the signals with the Signalyze program (InfoSignal, Inc., Lausanne, Switzerland).13 Peak oral air pressure during the voiceless plosive [p] was measured. We calculated the EGG signal slope, which reflects the relative closing speed of the glottis, as shown in Figure 2. Long-term average spectra (LTAS) were made on the vowel portion of the syllables (frequency range 5 kHz, logarithmic scale, bandwidth 20 Hz, time window 50 ms). Two values reflecting the spectral slope were calculated through subtraction (see Figure 3): (1) Difference in decibels between the level of the strongest spectral peak (L1) and the level of the fundamental frequency variation range (L0), from this on L1-L0, and (2) the difference between the level of the singer’s formant region (Ls) located between 2 kHz and 3 kHz and L1, from this on LsL1. We were interested in these level differences because they may reflect the type of voice production in terms of hypo/hyperfunctionality and register.14–16 Statistical analyses The intrarater and interrater reliability of the listening evaluations was studied with correlation analysis and Student t test. Analysis of variance was applied to explain the perceptual characteristics “support” and “quality.” Because the many variables and categories caused problems in the analysis of variance, we analyzed the independent variables’ relationships to the dependent variable with a genetic algorithm.17 Unlike traditional statistical
FIGURE 2. Calculation of the EGG signal slope, which reflects glottal closing speed. Steepness of the closing phase (decreasing impedance upward) relative to the horizontal base line is indicated with degrees. Journal of Voice, Vol. 19, No. 2, 2005
methods, a genetic algorithm is not based on strict formulas or assumptions about the data (such as linearity and normality of distribution). The algorithm makes small changes in the values and computes the effects of these changes on the efficacy of the prediction. Changes that improve the prediction are saved, and others are rejected. After many iterations, the values given to the predictors approach an optimal solution. The process is much like the development of species in nature, when beneficial mutations are saved and harmful ones destroyed, thus the term “genetic.” This kind of analysis is especially effective when the data are irregular and fuzzy and do not meet the assumptions of traditional statistical methods. The algorithm produces an estimate of each predictor’s relationship to the dependent variable. The strengths and forms of these relationships can then be calculated. When all relevant predictors are entered simultaneously, the method can most correctly share the variance between them. Relationships between acoustic/physiological variables and perception were also studied for men and women and for each task type separately with correlation analysis (Spearman) and t tests. RESULTS Reliability of evaluation Figure 4 illustrates the mean results of the evaluation of support in the same samples that were randomly replayed during the listening test. It can be seen that although variation occurred in the absolute estimate of support, the relationship between the samples with more support and those with less support was preserved. A significant correlation existed between the repetitive evaluations of the same samples (r ⫽ 0.85, P ⱕ .0001), and the two evaluations did not differ significantly from each other (t test). Thus, reliability of the first auditory impression may be regarded as good and the results obtained as valid. Differentiation of supported and unsupported voice by auditory impression For all three groups of listeners, the means for the evaluations statistically differed significantly between the samples produced with and without
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FIGURE 3. Description of the spectrum slope by calculating level differences between (1) the strongest peak in average spectrum and the fundamental frequency variation range (L1-L0) and (2) the singer’s formant region (between 2 kHz and 3 kHz) and the fundamental frequency variation range (Ls-L0). X-axis, frequency (Hertz) 0–2500 Hz, Y-axis, sound level (decibels), 10-dB division.
support (unpaired t test, P ⱕ .0001). It seems to be possible to distinguish supported singing from unsupported singing by impression. However, the difference was not categorical. Some support was heard in 46.2% of the samples of supported singing and in 30.5% of the samples of unsupported singing. Figure 5 illustrates the results of the evaluation by the listeners in Group C (N ⫽ 50), which consisted of trained singers, song pedagogues, and singing students. In general, the listeners heard more support in the samples produced with support than in the samples produced without support.
with each other (r ⫽ 0.81–0.85), and no statistically significant differences were found between them in t test either. Thus, singers and nonsingers did not seem to differ from each other in their evaluations of supported voice. “Supported singing” versus “supported voice” The singer subjects (listener Group A) heard more support in their own voice samples of supported singing than did the other singers in the
Trained versus untrained listeners Both singers and nonsingers showed much variation in their ratings of support. The evaluations given by the three groups of listeners correlated strongly
FIGURE 4. Repetitive evaluation of support in the same samples replayed randomly during the listening test.
FIGURE 5. Estimation of support by Group C (N ⫽ 50). Mean values of each listener’s evaluations of support in all samples of supported singing (black dot) and unsupported singing (white dot). Lines up or down show SD (one direction only for clarity). The listeners have been arranged in order according to the amount of support they heard in the samples). Journal of Voice, Vol. 19, No. 2, 2005
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listener group. Likewise, they also heard less support in their own voice samples of unsupported singing (Figure 6). Although the average of the singers’ estimation of their colleagues’ supported voices was 56.1% support, the average of the singers’ estimations of their supported voice samples was 64.7% support. The difference was statistically significant (P ⱕ .01). The mean of the singers’ evaluation of their unsupported voice samples was 30.9% support, whereas the mean of the singers’ evaluation of their colleagues’ unsupported samples was 33.1% support. This difference was also statistically significant (P ⱕ .0001). Relationship between “good” and “supported” voice The evaluations of the three listener groups correlated strongly with each other for both perceived support (r ⫽ 0.81–0.85) and voice quality
FIGURE 6. The average degree of support in each singer’s (indicated by initials) samples evaluated by the singers (vertical axis) and by all singers (horizontal axis). Journal of Voice, Vol. 19, No. 2, 2005
(r ⫽ 0.79–0.85). Sum scores were thus computed for both perceived support and voice quality. The sums correlated very strongly with each other (r ⫽ 0.92); this indicates that they were almost identical. This suggests either that “supported voice” and “good voice” are more or less the same thing or that the judges could not hear the difference between the two. Acoustic and physiological correlates of good/supported voice Because the supported voice apparently was “a good voice,” the sum score “voice quality” was taken to be the dependent variable in further statistical analyses. The following results were obtained with genetic algorithm. Figure 7 illustrates the average relationships among subglottic pressure, EGG slope, spectrum parameters, and perceived voice quality, obtained with the genetic algorithm. Quality was evaluated as best when subglottic pressure was between 9.9 and 13.4 cm H2O. Voice quality, in turn, was evaluated as best when EGG slope was between 49⬚ and 63⬚. The relationships between perceived voice quality/ estimate of support and the values calculated from the spectra were dualistic. Voice quality was evaluated as best when the level difference between L1 and L0 was either between ⫺13.9 and ⫺4.7 dB or between ⫹4.3 and ⫹3.4 dB. Similarly, best voice quality seemed to be reached when the level difference between the singer’s formant region and L1 was either between ⫺30.5 and ⫺21.9 dB or between ⫺4.7 and ⫹3.8 dB. These two ranges for optimum result can be explained as reflecting different quality criteria for male and female voices and for different task types. The genetic algorithm shows the average tendencies more clearly. On the basis of mean results, however, it is not possible to draw any far-reaching conclusions. Figure 8 shows scatter plots between the evaluations of voice quality and the acoustic and physiological parameters for all samples. No correlations can be found when all samples from both men and women produced at different pitch and loudness levels are treated together. Therefore, correlation analyses were made for male and female voices and for different task types separately (Table 2).
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FIGURE 7. Relations between perceived voice quality and acoustic/physiological variables as obtained with the genetic algorithm. Ps ⫽ subglottic (oral) pressure, EGG slope ⫽ steepness of the closing phase of the electroglottographic signal, L1-L0 ⫽ level difference between the strongest peak in average spectrum and the fundamental frequency variation range, and Ls-L0 ⫽ level difference between the singer’s formant region (between 2 kHz and 3 kHz) and the fundamental frequency variation range.
In Table 2, a positive correlation existed between Ps (oral) and voice quality in intensity variation (pp-ff-pp) for women at both pitches and for men at high pitch. For the men, in intensity variation at low
pitch, the relation between Ps and voice quality was polynomial, which suggests that the best voice quality was reached when Ps obtained intermediate values. The relationship between EGG slope and Journal of Voice, Vol. 19, No. 2, 2005
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FIGURE 8. Scattergrams of perceived voice quality and acoustic/physiological variables. Ps ⫽ subglottic (oral) pressure, EGG slope ⫽ steepness of the closing phase of the electroglottographic signal, L1-L0 ⫽ level difference between the strongest peak in average spectrum and the fundamental frequency variation range, and Ls-L0 ⫽ level difference between the singer’s formant region (between 2 kHz and 3 kHz) and the fundamental frequency variation range.
voice quality also was polynomial for both men and women in intensity variation at low pitch and in sustained phonation at high pitch in male singers. For women, in intensity variation at high pitch, the EGG slope correlated positively with voice quality. For women, the level differences L1-L0 and Ls-L1 correlated negatively with perceived voice quality. In male singers, both correlations were positive at high pitch in sustained phonation, but only L1-L0 correlated significantly with voice quality in pp-ffpp variation. These findings suggest that a steeper spectral slope (relatively weaker L1 and Ls and/ or stronger fundamental) was regarded as positive in the female singers, but the opposite was true for the male singers. Journal of Voice, Vol. 19, No. 2, 2005
To find more precise acoustic/physiological correlates of quality, samples with the highest and the lowest percentage of support (best and poorest voice quality) were compared in each task and for men and women separately. Table 3 shows the average results and the significance of differences (t test) in the parameters. Ps varied between 6 and 13 cm H2O in the best samples of the female singers in this material, EGG slope between 44⬚ and 54⬚, L1-L0 between ⫺4 and ⫺8 dB, and Ls-L0 between ⫺18 and ⫺22 dB. For the men, the variation for the best samples was Ps 5–10 cm H2O, EGG slope 37⬚ to 54⬚, L1-L0 ⫹8 to ⫹14 dB, and Ls-L0 ⫺9 to ⫹2 dB. In the female singers’ samples with the lowest percentage of support, Ps was lower, EGG
SUPPORT IN SINGING TABLE 2. Correlations (Spearman; * ⫽ polynomial, order 2) Between Perceived Voice Quality and Acoustic Parameters for Male and Female Subjects in Various Tasks (number of samples 40 for females, 24 for males) FEMALES (N ⴝ 5)
MALES (N ⴝ 3)
(1) Sustained phonation Ps EGG slope L1-L0 Ls-L0
Low NS NS ⫺0.64 P ⫽ 0.001 ⫺0.61 P ⫽ .002
High NS NS ⫺0.61 P ⫽ 0.004 ⫺0.46 P ⫽ .04
Low NS NS NS
Low 0.82 P ⫽ .000 0.61* P ⫽ .029 ⫺0.66 P ⫽ .001 ⫺0.62 P ⫽ .002
High 0.55* P ⫽ .033 0.65 P ⫽ .004 ⫺0.50 P ⫽ .018 ⫺0.43 P ⫽ .044
Low 0.77* P ⫽ .011 0.86* P = .001 NS
NS
High NS 0.67* 0.64 P ⫽ .006 0.60 P ⫽ .012
(2) pp-ff-pp Ps EGG slope L1-L0 Ls-L0
NS
High 0.56 P ⫽ .046 NS 0.96 P ⫽ .000 NS
Low/high ⫽ pitch below/above the first register transition. Ps ⫽ subglottic (oral) pressure. EGG slope: L1-L0 ⫽ level difference between the strongest peak in average spectrum and the fundamental frequency variation range. Ls-L0 ⫽ level difference between singer’s formant region (between 2 kHz and 3 kHz) and the fundamental frequency variation range.
slope was higher at low pitch and lower at high pitch, and both L1-L0 and Ls-L0 were smaller. In the men, the poorest samples had higher Ps and EGG slope at low pitch and lower at high pitch; both L1L0 and Ls-L0 were smaller. In general, even in the best samples, the mean evaluation of support varied between 50.9% and 68.2% for the women and between 35.2% and 47.4% for the men. Figure 9 illustrates the spectral differences between the best male and female voices in the material. L0 is clearly weaker compared with L1 in the good male voice, whereas the opposite can be seen in the female voice. Ls is stronger in relation to L0 in the male voice than in the female voice. DISCUSSION Singers often seem to have very strong opinions about support in singing. However, these opinions
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are often quite different. Although, for example, Domingo claims he has obtained the finest control over his voice through support, Stampa rejects the concept “support” as harmful for the voice.3 The reason for these discrepancies may lie in terminological differences. In this study, the singers were assumed to know themselves, when they are singing with and without support. Interestingly, three of the seven subjects could not auditively distinguish between their samples produced with and without support. These samples also caused difficulties to other listeners. In general, listeners often disagreed on various samples: The same sample could be evaluated as representing almost no support at all and 100% of support. One singing pedagogue could not hear any really supported voice among the test samples. In spite of disagreements for various samples, the statistical treatment showed certain clear tendencies among the listeners’ evaluations. In the average, the listeners were by first impression able to differentiate between supported and unsupported voice samples. On the other hand, voice quality and support could not be distinguished in the listening evaluations. Thus, from the listener’s point of view, “supported voice” seems to be nothing but “good voice.” It seems to be a subjective choice, then, whether a person calls a good voice also a supported voice. “Good” should not be considered equivalent to “beautiful” because that, in turn, is much more a matter of subjective taste. The procedure of this study might have affected the results. When the subjects sang “with support,” they most likely sang as well as they possibly could, whereas when mimicking singing “without support,” it is possible that they just tried to sing less well. On the other hand, these professional singers were also song pedagogues, and it seems plausible that they can mimic different characteristics in singing. It is likely that, for some singers, “support” is an important tool for producing a good voice quality, whereas for others, “support” evokes images that might have a harmful effect on effortless phonation. Earlier studies9,10 on the differences between supported and unsupported singing have suggested that supported singing is, for example, characterized by a longer maximum phonation time, lower vertical laryngeal position (at least in men), higher subglottic Journal of Voice, Vol. 19, No. 2, 2005
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A. SONNINEN ET AL TABLE 3. Differences (Mean, SD in Parentheses) Between the Samples With Best and Poorest Voice Quality (Highest/Lowest % of Support) in Each Task
Females (N 5) (1) Sustained phonation Low Good Poor Sign. High Good Poor Sign. (2) pp-ff-pp Low Good Poor Sign. High Good Poor Sign. Males (N 3) (1) Sustained phonation Low Good Poor Sign. High Good Poor Sign. (2) pp-ff-pp Low Good Poor Sign. High Good Poor Sign.
Ps (cm H20)
EGG slope (⬚)
L1-L0 (dB)
Ls-L0 (dB)
Support (%)
8.6 (6.2) 7.0 (2.2) NS 5.7 (1.7) 6.3 (2.2) NS
52.1 (14.9) 60.7 (17.6) NS 48.1 (13.5) 40.0 (17.4) NS
⫺7.7 (4.0) 7.4 (4.4) P ⴝ .000 ⫺8.5 (8.4) 10.0 (7.1) P ⴝ .006
⫺22.2 (3.9) ⫺5.6 (10.8) P ⴝ .012 ⫺20.1 (6.7) ⫺3.3 (9.4) P ⴝ .012
67.5 (1.6) 18.5 (9.4) P ⴝ .000 50.9 (4.0) 11.0 (3.2) P ⴝ .000
13.0 (1.5) 5.4 (2.2) P ⴝ .000 9.1 (1.3) 5.2 (1.0) P ⴝ .001
43.9 (11.2) 53.3 (21.0) NS 54.0 (5.8) 30.8 (8.7) P ⴝ .001
⫺4.0 (7.3) 8.1 (4.5) P ⴝ .013 ⫺8.1 (8.0) 2.4 (2.3) P ⴝ .023
⫺17.6 (4.3) ⫺4.6 (4.8) P ⴝ .002 ⫺20.8 (0.9) ⫺10.5 (2.3) P ⴝ .000
68.2 (5.5) 34.3 (3.5) P ⴝ .000 57.3 (9.8) 9.1 (2.5) P ⴝ .000
9.7 (5.2) 11.2 (4.3) NS 5.0 (1.2) 4.4 (0.9) NS
53.9 (18.2) 45.4 (14.8) NS 50.0 (0.6) 31.3 (16.7) P ⴝ .035
13.7 (3.8) ⫺7.8 (14.8) P ⴝ .014 12.9 (1.2) ⫺1.9 (3.2) P ⴝ .000
⫺1.4 (2.4) ⫺17.5 (10.1) P ⴝ .008 ⫺6.6 (3.6) ⫺15.7 (2.0) P ⴝ .001
41.4 (6.2) 22.3 (5.4) P ⴝ .001 35.2 (6.2) 14.0(4.4) P ⴝ .000
9.7 (1.5) 13.0 (2.5) P ⴝ .036 7.5 (2.5) 4.3 (2.2) NS
36.7 (18.3) 58.7 (12.8) NS 37.0 (2.2) 30.3 (18.5) NS
14.1 (3.4) 5.4 (10.9) NS 8.5 (3.2) ⫺1.1 (3.3) P ⴝ .002
2.0 (2.1) ⫺3.7 (11.9) NS ⫺8.7 (6.5) ⫺8.4 (4.2) NS
47.4 (9.4) 25.7 (3.1) P ⴝ .001 40.2 (11.8) 11.3 (3.4) P ⴝ .001
Sign. ⫽ significance of difference, obtained with Student’s unpaired t test. Low/high ⫽ pitch below/above the first register transition. Ps ⫽ subglottic (oral) pressure. EGG slope ⫽ steepness of the closing phase (decreasing impedance). L1-L0 ⫽ level difference between the strongest peak in average spectrum and the fundamental frequency variation range. Ls-L0 ⫽ level difference between singer’s formant region (between 2 kHz and 3 kHz) and the fundamental frequency variation range.
pressure, higher peak airflow, higher glottal closing speed, and a less steep spectral slope than unsupported singing. The results of this study, in turn, suggest that the difference between supported and unsupported voice—that is, the difference between good and poor voice quality—is not categorically dualistic, but it is gender and task dependent. In some tasks, Ps was higher in good/supported voice, but in others either no significant correlation existed between Ps and perceived support or the relationship was polynomial; this suggests that the optimum would be reached at intermediate subglottic pressure values. The results were similar for EGG slope, which Journal of Voice, Vol. 19, No. 2, 2005
reflects glottal closing speed. As could be expected, the ideal spectrum slope was different for male and female singing and for different singing tasks. In general, a steeper slope (lower values for L1-L0 difference, ie, a weaker L1 or a stronger L0, and higher absolute values for the Ls-L0 difference, ie, a weaker Ls) was related to better voice quality in female singing, whereas the opposite was observed in male singing, especially at high pitch. Vennard8 defined support as a good control of subglottic pressure. According to Hirano,18 subglottic pressure varies approximately between 2 cm H2O and 50 cm H2O in singing, depending on the singing
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FIGURE 9. Long-term average spectrum of the samples that were evaluated as having most support.
style and the method used by the researcher for measurement. Subglottic pressure is lower in piano (about 5 cm H2O) than in forte (about 20 cm H2O). Subglottic pressure also generally rises with pitch. In our study, subglottic pressure varied between 5 and 13 cm H2O in the samples that were perceived as best in quality. Samples with the poorest quality obtained higher or lower mean Ps values, which does not mean that in all good singing, Psub should be in that range. Instead, the results suggest that, although Psub naturally varies according to pitch and loudness, from the point of view of perception, the
best samples these subjects produced in this study had intermediate Psub values, which in these tests happened to be in that range. Most likely, this result reflects the type of voice production. Deviation from the optimum toward higher subglottic pressure values may be related to a shift from flow phonation to pressed phonation, whereas lower-than-optimum pressure values may be obtained in breathy, hypofunctional voice production.16,18 Although the absolute values for the “optimum” glottal closing speed naturally vary depending on gender, pitch, intensity, register, voice category, and Journal of Voice, Vol. 19, No. 2, 2005
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so on, the polynomial relation between EGG slope and perceived voice quality seems to suggest a relative optimum in glottal closing speed. This is in line with the observations of Verdolini et al19 on “resonant voice.” Because subglottic pressure needs to vary according to pitch and loudness, the optimal glottal closing speed cannot be just a result of certain subglottic pressure. Instead, optimal glottal closing speed requires glottal adjustment, which may belong to the concept of “support” in light of the results from this study. These adjustments could consist of optimal prephonatory size of the glottis and optimal stiffness of the vocal folds: because the prephonatory size of the glottis is small, as it is in pressed phonation, the glottal closing speed is higher than normal, and in contrast, when the size of the glottis is relatively large, the voice production is asthenic, and the relative glottal closing speed is low. Furthermore, in the falsetto register, the relative vocalis activity is lower,20 and therefore, the membranous portion of the vocal folds, the cover, is stiff. Thus, the relative glottal closing speed is lower than in modal register, in which the cover is lax and pliable. The vibratory mode of the vocal folds also determines the spectral characteristics of the voice: Spectral slope becomes less steep as the glottal closing speed increases and vice versa.14 Steeper spectral slope in female voices suggests a more falsetto type of phonation. In high pitches, it may also reflect formant tuning, ie, a coincidence of the fundamental and the first formant, which boosts L1 considerably.16,21 In male voices, a less steep slope (stronger L1 and Ls) suggests both a more chest register type of phonation (with stronger harmonics per se) and resonance effects: Raising F1 higher than the fundamental and tuning it to an overtone (or tuning of the second formant to an overtone) boosts L1 (or L2, ie, the level of the second formant region) and may help to keep the voice masculine even at high pitches,22 whereas a strong singer’s formant is needed to obtain a desirable ringing quality and a sufficient audibility in the male voice. If support means control of subglottic pressure, it must in practice mean a constantly varying active cooperation between various muscles. Subglottic pressure varies according to lung volume, tending to be high when lung volume is high (after deep inspiration) and low when lung volume is low (after Journal of Voice, Vol. 19, No. 2, 2005
long/forceful expiration). To keep subglottic pressure constant when needed for a certain pitch and loudness, these lung-volume related pressure changes need the compensation of the inspiratory muscles at the beginning of the phrase and the expiratory muscles at the end of the phrase (Figure 10). The function of respiratory muscles in the control of subglottic pressure is different in forte than in piano singing. “Rib reserve”24 can be used by the singer without compensation of inspiratory muscles at the beginning of forte phonation. Function of the expiratory muscles is needed more in forte than in piano singing. So the contraction of the respiratory muscles in singing cannot be static. As the results of Nadoleczny6 and Schilling7 in the beginning of the 20th century and the recent results of Thomasson and Sundberg25 show, singers use different breathing patterns. This means that the goal, control of subglottic pressure, can be achieved in different ways. For a simplified analogy, in playing the accordion, the sound can be produced in three ways: (1) by pressing the bellows with both hands, (2) by pressing the bellows with the left hand while keeping the right hand still, or (3) by pressing the bellows with the right hand while keeping the left one still. Most likely, the pressure control can be performed more accurately in the second and third ways when the passive part (hand still) gives support and helps in concentrating on the function of the active part in the “controlling system.” In voice production, three basic alternatives are offered to control subglottic pressure: (1) both the abdominal and thoracic muscles are active, (2) abdominal muscles are active and thoracic muscles are more or less passive, or (3) thoracic muscles are active and abdominal muscles are more passive. Both abdominal and thoracic muscles can be involved in the control of subglottic pressure when needed (Figure 9). In 13 of the 30 singers interviewed by Hines,3 the description of support in singing seems to agree well with the concept of thoracic support by Schilling.7 There, “the chest maintains the inspiratory position for a longer time, while the diaphragm ascends gradually.” On the other hand, obviously singers using diaphragmatic support exist, in which “the diaphragm maintains its inspiratory descended position for a longer period of phonic expiration (up to 8 seconds). At the same time, the elevated chest
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FIGURE 10. Control of subglottic pressure through cooperation between inspiratory (arrows to the left) and expiratory (arrows to the right) muscle activity. Figure adapted from Draper et al.23
descends slowly, liberating the respiratory energy, which was accumulated through maximal inspiration, by pectoral expiration.”7 Singers typically have strong ideas of their breathing pattern, but the results
of Watson and Hixon26 have shown that the ideas are not necessarily related to objectively measurable events. However, the results obtained by Thomasson and Sundberg25 suggest that singers are consistent Journal of Voice, Vol. 19, No. 2, 2005
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in their breathing patterns; ie, they repeatedly use the same pattern for the same singing tasks. Type of breathing is related to the vertical position of the larynx and to phonation type. As the diaphragm descends, the larynx is also pulled down.27,28 This, in turn, poses an abductory tendency on the glottis. Control of the diaphragm is related to flow phonation, characterized by a relatively large glottal airflow.28 Furthermore, phonation at a larger lung volume is related to a lower position of the larynx and flow phonation.29 Type of breathing per se does not necessarily determine the type of support exploited. However, the so-called costo-abdominal breathing in which the diaphragm descends and the rib cage expands during inspiration offers the best possibilities to choose between types of support. The choice, in turn, may even be related to the singer’s body type. Subglottic pressure, the driving force of the vocal fold vibration, is determined not only by respiratory activity but also by the combination of respiratory and glottal factors. Thus, support should be a dynamic phenomenon requiring varying and correctly timed, well-coordinated contraction of respiratory and phonatory muscles to control subglottic pressure adequately. The sensation “press-counterpress, one in balance against the other” reported by some singers (eg, Crespin in Hines3) could be related to this coordination. The inertia of the air column of the vocal tract, which can be controlled by widening and narrowing the vocal tract, might also play a role in the delicate control of voice production during singing and contribute to the singers’ subjective sensations of support. CONCLUSIONS 1. It is possible to differentiate between supported and unsupported voice samples by impression. 2. Trained singers and nonsingers did not differ significantly in their abilities to evaluate support. 3. Singers evaluated their samples of supported singing as having more support than did the other listeners, and similarly, the singers heard less support in their samples of unsupported singing. Journal of Voice, Vol. 19, No. 2, 2005
4. From the point of view of perception, “supported voice” was the same as “good voice.” 5. The results suggest that although the absolute values for Ps and EGG slope may be gender and task dependent, best voice quality is characterized by intermediate Ps and EGG slope values and, thus, neither pressed nor breathy phonation. Good voice quality in female singing requires a sufficiently steep spectral slope, whereas, in male singing, a less steep spectrum slope is appreciated.
Acknowledgments: The authors thank the subjects and the listening panel. Mr. Timo Honkonen, singing pedagogue, and Professor Paavo Malinen, expert in mathematics, are also thanked for fruitful discussions.
REFERENCES 1. Sonninen A, Hurme P. Clinical voice evaluation: holistic viewpoints. In: Loebell E, editor. Proceedings of II World Congress of the International Association of Logopedics and Phoniatrics, Hannover August 9–14, 1992, pp. 29–32. 2. Sonninen A. Ontology and communication in speech and voice therapy. Nordisk Logopedi og Foniatri Status og Udvikling. In: Kjær BE, editors. Tredje Nordiska Kongressen fo¨r Logopedi och Foniatri, Go¨teborg, October 6–9, 1994, pp. 14–24. 3. Hines J. Great singers on great singing. London: Victor Gollanez; 1983. 4. Haskell J. Vocal self-perception: the other side of the equation. J Voice. 1987;1:172–179. 5. Sonninen A, Hurme P. On the terminology of voice research. J Voice. 1992;6:188–193. 6. Nadoleczny M. Untersuchungen u¨ber den Kunstgesang. Berlin: Verlag von Julius Springer; 1923. 7. Schilling R. Untersuchungen u¨ber die Atembewegungen beim Sprechen und Singen. Mschr. Ohrenheilk. 1925;59:51. 8. Vennard W. Singing: the mechanism and the technic. New York: Fischer; 1967. 9. Sonninen A, Hurme P, Sundberg J. Physiological and acoustic observations of support in singing. In: Friberg A, Iwarsson J, Jansson E, Sundberg J, editors. SMAC 93 Proceedings of the Stockholm Music Acoustic Conference July 28–August 1, 1993. Royal Swedish Academy of Music No. 79, pp. 254–258. 10. Griffin B, Woo P, Colton R, Casper J, Brewer D. Physiological characteristics of the supported singing voice. A preliminary study. J Voice. 1995;9:45–56. 11. Rothenberg M. A multichannel electroglottograph. J Voice. 1992;6:36–43.
SUPPORT IN SINGING 12. Lo¨fqvist A, Carlborg B, Kitzing P. Initial validation of an indirect measure of subglottal pressure during vowels. J Acoust Soc Amer. 1982;72:633–635. 13. Keller E. Signalyze Version 3.0: Signal analysis for speech and sound. User’s Manual. Lausanne: InfoSignal Inc.; 1994. 14. Gauffin J, Sundberg J. Spectral correlates of glottal voice source waveform characteristics. J Speech Hear Res. 1989; 32:556–565. 15. Kitzing P. LTAS criteria pertinent to the measurement of voice quality. J Phon. 1986;14:477–482. 16. Sundberg J. The science of the singing voice. Dekalb: Northern Illinois University Press; 1987. 17. Goldberg D. Genetic algorithms. Reading, MA: Addison Wesley; 1988. 18. Hirano M. Clinical examination of voice. In: Arnold GE, Winckel F, Wyke BD, editors. Disorders of human communication 5. Wien: Springer Verlag; 1981. 19. Verdolini K, Druker DG, Palmer PM, Samawi H. Laryngeal adduction in resonant voice. J Voice. 1998;12:315–327. 20. Hirano M. Vocal mechanisms in singing: laryngological and phoniatric aspects. J Voice. 1988;2:51–69. 21. Sundberg J. Formant technique in professional female singer. Acustica. 1975;32:89–96.
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22. Titze IR, Mapes S, Story B. Acoustics of the tenor high voice. J Acoust Soc Amer. 1994;95:1133–1142. 23. Draper MH, Ladefoged P, Whitteridge D. Respiratory muscles in speech. J Speech Hear Res. 1959;2:16–27. 24. Hoit JD, Banzett RB, Brown R, Loring SH. Speech breathing in individuals with cervical spine cord injury. J Speech Hear Res. 1990;33:798–807. 25. Thomasson M, Sundberg J. Consistency of phonatory breathing patterns in professional operatic singers. J Voice. 1999;13:529–541. 26. Watson PJ, Hixon TJ. Respiratory kinematics in classical (opera) singers. In: Hixon TJ, editor. Respiratory function in speech and song. Boston: Taylor & Francis Ltd.; 1987: 337–374. ¨ ber die Regelung der Stimmlippens27. Zenker W, Zenker A. U pannung durch von aussen eingreifende Mechanismen. Folia Phoniatrica, 1960;12:1–36. 28. Leanderson R, Sundberg J, von Euler C. Role of diaphragmatic activity during singing: a study of transdiaphragmatic pressures. J Appl Physiol. 1987;62:259–270. 29. Iwarsson J, Thomasson M, Sundberg J. Effects of lung volume on the glottal voice source. J Voice. 1998;12: 424–433.
Journal of Voice, Vol. 19, No. 2, 2005
Summary: This study searched for perceptual, acoustic, and physiological correlates of support in singing. Seven trained professional singers (four women and three men) sang repetitions of the syllable [pa:] at varying pitch and sound levels (1) habitually (with support) and (2) simulating singing without support. Estimate of subglottic pressure was obtained from oral pressure during [p]. Vocal fold vibration was registered with dual-channel electroglottography. Acoustic analyses were made on the recorded samples. All samples were also evaluated by the singers and other listeners, who were trained singers, singing students, and voice specialists without singing education (a total of 63 listeners). We rated both the overall voice quality and the amount of support. According to the results, it seemed impossible to observe any auditory differences between supported singing and good singing voice quality. The acoustic and physiological correlates of good voice quality in absolute values seem to be gender and task dependent, whereas the relative optimum seems to be reached at intermediate parameter values. Key Words: Self-perception—Acoustic and perceptual voice quality— Electroglottography—Subglottic (oral) pressure—Spectrum—Breathing— Singing technique.
is singing with support or without it. Thus, the word support is also used by evaluators when assessing the perceptual singing voice quality and the presumed physiological background of it. Support, then, is a sensation that both singers and listeners have,1,2 at least when the listeners have experience in singing. Many singers regard support as essential in singing. As the world-famous soprano Birgit Nilsson puts it, “If one forgets the support, it’s [voice] like a flower without roots; after a while it begins to fade.”3 This self-perception4 must somehow be described.5 Support is closely connected with respiration, which can be reflected in the expressions: “breath support” and “Atemstu¨tze.” Sometimes in English, singers use metaphors such as “lean” or “rest on the voice.” Singing pedagogy mainly operates with the sensations of the singer and the listener. Researchers of singing, in turn, are more interested in the physiological and acoustic variables. Nadoleczny6 found in his profound study that 40% of singers
INTRODUCTION Support (appoggio in Italian, appui in French, Stu¨tze in German, sto¨d in Swedish, and tuki in Finnish) is a concept widely used by classically trained operatic singers. It refers to a sensation singers have during singing. In addition, it is often claimed that a trained ear can immediately hear whether someone
Accepted for publication August 2, 2004. From the *Department of Communication, University of Jyva¨skyla¨, Jyva¨skyla¨, Finland; †Department of Speech Communication and Voice Research, University of Tampere, Tampere, Finland; ‡Sibelius Academy, Helsinki; Finland. Address correspondence and reprint requests to Professor Aatto Sonninen, MD, PhD, Gummeruksenk. 3 B 24, 40100 Jyva¨skyla¨, Finland. E-mail: [email protected] Journal of Voice, Vol. 19, No. 2, pp. 223–237 0892-1997/$30.00 쑕 2005 The Voice Foundation doi:10.1016/j.jvoice.2004.08.003
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(N ⫽ 92) used combined “costo-abdominal” breathing, and 25% mainly used “costal breathing” for supported singing. (These terms refer to the observable inspiratory movements of the chest and abdomen.) According to Nadoleczny, support is a sensation caused by muscle and pressure receptors during expiration. According to the radiological studies undertaken by Schilling,7 two main types of support can be distinguished: diaphragmatic support and thoracic support. Vennard8 defines support as well-controlled respiratory [subglottic] pressure. Recent research on support seems to be shifting in medias res from breathing to the acoustic, aerodynamic, and physiological phenomena of voice production. Sonninen et al9 studied physiological and acoustic differences between supported and unsupported singing in nine professional classically trained singers. According to the results, supported singing was characterized by a longer maximum phonation time, lower vertical position of the larynx, higher subglottic (oral) pressure, faster glottal closing speed, and especially in male singers, a greater difference between the first formant region and the fundamental. Griffin et al10 found higher SPL, higher average and peak airflow, and lower open quotient of the glottis in supported singing compared with unsupported singing. F4 was also lower in supported singing. Griffin et al also questioned the singers about their definition of support. All subjects associated support with management of breathing and described supported singing as having better tone quality and greater ease of management. The present investigation aimed to study the perception of support and its relationship to physiological and acoustic variables. Aims of the study This study aimed to find answers to the following questions: 1. Is it possible to distinguish between supported and unsupported voices by auditory impression? 2. Do trained singers and nonsingers differ in their perceptions of supported and unsupported singing? 3. How is self-perception of support (singer as subject) related to auditory evaluation of support in one’s own recorded voice (same singer as object)? Journal of Voice, Vol. 19, No. 2, 2005
4. What is the relationship between “supported voice” and “good voice”? 5. What acoustic and physiologic parameters, if any, correlate with good and/or supported voice? It is important to note the ontological dimensions of the object of the present study (questions 4 and 5). For clarity, supported singing refers to something that the singer does and senses, whereas supported voice refers to something that the listener perceives and that, therefore, has acoustic correlates. METHODS Subjects Four female and three male professional singers volunteered as subjects in this study (Table 1). The subjects represented various voice types. They were aged 25 to 84 years. (The oldest subject, Vilho Kekkonen, has been registered in the Guinness Book of Records 1991 and 1996 as the oldest tenor who has given a concert.) Tasks We recorded the subjects in a quiet room when singing in upright position. They produced syllable sequences [pa: pa: pa:] at two pitches above and below the register transition area (from this on: high/ low pitch), which is common for both men and women (about C4 and G4). The subjects were instructed to produce the syllables (1) for at least 5 seconds at a constant pitch and loudness and (2) with varying intensity (pp – ff – pp) and (3) with a melodic figure (Figure 1), first with support and then immediately without support. The presupposition was that professional singers can sing with and without support. Recordings The acoustic signals were recorded on a tape recorder (Revox, Regensdorf, Switzerland) with a 30-cm mouth-to-microphone distance. Electroglottographic (EGG) signals were obtained with a dualchannel electroglottograph11 and recorded with the acoustic signals on a Revox tape recorder. Intraoral air pressure (DC) signals were registered with a manometer and recorded with a Racal Thermionic
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TABLE 1. Sex, Age, Voice Class, Voice Range, and Training of the Subjects Case
Sex
Class
Age yrs
a yrs
b yrs
c lowest
d transition
e highest
ST RV MH HV VK mean F G H mean
F F F F F
Mezzo-soprano Lyric soprano Dramatic soprano Soprano Lyric soprano
25.0 26.0 64.0 39.0 36.0 38.0 52.0 64.0 84.0 66.7
18.0 21.0 17.0 18.0 18.0 18.4 21.0 21.0 20.0 20.7
6.0 4.0 30.0 6.0 22.0 13.6 10.0 15.0 15.0 13.3
D3 E3 A3 D3 G3 E3-F3 E2 A2 C3 G#2
C4 E4 F4 F4 E4 D#4 E4 F4 F4 F4
A#5 D6 A5 D6 C6 B5–C6 G4 A4 C5 A4
M M M
Baritone Baritone Tenor
a: Age when vocal education started; b: duration of vocal education; c: lowest pitch; d: first register transition (for the females, second for the males); e: highest pitch. yrs ⫽ years. F ⫽ female. M ⫽ male.
instrumentation recorder (Racal Instruments, Irvine, Calif). Pressure was calibrated into centimeters of water (cm H2O) with a u-tube manometer. Intraoral pressure provided an estimate of subglottic pressure.12 Listening evaluation Three groups of listeners (N ⫽ 63) attended the listening evaluation. Group A consisted of the singers. Group B consisted of two amateur singers and three voice researchers without singing training. One of the amateur singers evaluated the samples twice. Group C (N ⫽ 50) consisted of student singers from the Sibelius Academy (N ⫽ 32) and professional singers and singing pedagogues (N ⫽ 18). The test tape included 170 randomized samples, each of 5-second duration (subjects ⫽ 8; task type ⫽ 3: sustained phonation, variation of loudness, melodic figure; pitch ⫽ 2: low, high; singing type ⫽ 2: with support/without support; thus, the basic number of samples was 8 × 3 × 2 × 2 ⫽ 96. Additionally, to study the reliability of the listening
FIGURE 1. Melodic figure sung by the subjects.
evaluation, 12 randomly chosen samples were repeated two to four times, summing up 33 samples, at random intervals during the listening test, especially close to the end of the test. Furthermore, in the case of very long, over 10 seconds, syllable sequences produced at constant pitch and loudness, we presented the listeners with a 5-second sample from both the beginning and the end of the sequence, resulting in 41 more samples. Thus, the number of samples presented to the listeners was 170). Three listening tests were conducted: Groups A and B listened to the samples in the same conditions, in an ordinary low noise room in free field. The listening evaluation for Group C was arranged in free field in a large auditorium in Sibelius Academy. All listening tests were carried out about 2 months after the recording sessions. The reason for this delay was to obtain from the singers evaluations of their samples that were as objective as possible. The listeners had two tasks: to evaluate the amount of “support” and to evaluate the voice quality in the samples. Both variables were evaluated on a continuous visual-analogous scale (VAS) from no support to 100% of support and from very poor quality to very good quality (0% to 100%). No definitions of support or quality were given to the listeners. The listeners’ first auditory impression was the object of interest. Therefore, only a 5-second pause was given between the samples. The listeners were allowed a repetition of a sample if necessary. Journal of Voice, Vol. 19, No. 2, 2005
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However, repetitions were requested only a few times during the tests. The duration of the test was about 40 minutes. Analyses We made all physical analyses of the signals with the Signalyze program (InfoSignal, Inc., Lausanne, Switzerland).13 Peak oral air pressure during the voiceless plosive [p] was measured. We calculated the EGG signal slope, which reflects the relative closing speed of the glottis, as shown in Figure 2. Long-term average spectra (LTAS) were made on the vowel portion of the syllables (frequency range 5 kHz, logarithmic scale, bandwidth 20 Hz, time window 50 ms). Two values reflecting the spectral slope were calculated through subtraction (see Figure 3): (1) Difference in decibels between the level of the strongest spectral peak (L1) and the level of the fundamental frequency variation range (L0), from this on L1-L0, and (2) the difference between the level of the singer’s formant region (Ls) located between 2 kHz and 3 kHz and L1, from this on LsL1. We were interested in these level differences because they may reflect the type of voice production in terms of hypo/hyperfunctionality and register.14–16 Statistical analyses The intrarater and interrater reliability of the listening evaluations was studied with correlation analysis and Student t test. Analysis of variance was applied to explain the perceptual characteristics “support” and “quality.” Because the many variables and categories caused problems in the analysis of variance, we analyzed the independent variables’ relationships to the dependent variable with a genetic algorithm.17 Unlike traditional statistical
FIGURE 2. Calculation of the EGG signal slope, which reflects glottal closing speed. Steepness of the closing phase (decreasing impedance upward) relative to the horizontal base line is indicated with degrees. Journal of Voice, Vol. 19, No. 2, 2005
methods, a genetic algorithm is not based on strict formulas or assumptions about the data (such as linearity and normality of distribution). The algorithm makes small changes in the values and computes the effects of these changes on the efficacy of the prediction. Changes that improve the prediction are saved, and others are rejected. After many iterations, the values given to the predictors approach an optimal solution. The process is much like the development of species in nature, when beneficial mutations are saved and harmful ones destroyed, thus the term “genetic.” This kind of analysis is especially effective when the data are irregular and fuzzy and do not meet the assumptions of traditional statistical methods. The algorithm produces an estimate of each predictor’s relationship to the dependent variable. The strengths and forms of these relationships can then be calculated. When all relevant predictors are entered simultaneously, the method can most correctly share the variance between them. Relationships between acoustic/physiological variables and perception were also studied for men and women and for each task type separately with correlation analysis (Spearman) and t tests. RESULTS Reliability of evaluation Figure 4 illustrates the mean results of the evaluation of support in the same samples that were randomly replayed during the listening test. It can be seen that although variation occurred in the absolute estimate of support, the relationship between the samples with more support and those with less support was preserved. A significant correlation existed between the repetitive evaluations of the same samples (r ⫽ 0.85, P ⱕ .0001), and the two evaluations did not differ significantly from each other (t test). Thus, reliability of the first auditory impression may be regarded as good and the results obtained as valid. Differentiation of supported and unsupported voice by auditory impression For all three groups of listeners, the means for the evaluations statistically differed significantly between the samples produced with and without
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FIGURE 3. Description of the spectrum slope by calculating level differences between (1) the strongest peak in average spectrum and the fundamental frequency variation range (L1-L0) and (2) the singer’s formant region (between 2 kHz and 3 kHz) and the fundamental frequency variation range (Ls-L0). X-axis, frequency (Hertz) 0–2500 Hz, Y-axis, sound level (decibels), 10-dB division.
support (unpaired t test, P ⱕ .0001). It seems to be possible to distinguish supported singing from unsupported singing by impression. However, the difference was not categorical. Some support was heard in 46.2% of the samples of supported singing and in 30.5% of the samples of unsupported singing. Figure 5 illustrates the results of the evaluation by the listeners in Group C (N ⫽ 50), which consisted of trained singers, song pedagogues, and singing students. In general, the listeners heard more support in the samples produced with support than in the samples produced without support.
with each other (r ⫽ 0.81–0.85), and no statistically significant differences were found between them in t test either. Thus, singers and nonsingers did not seem to differ from each other in their evaluations of supported voice. “Supported singing” versus “supported voice” The singer subjects (listener Group A) heard more support in their own voice samples of supported singing than did the other singers in the
Trained versus untrained listeners Both singers and nonsingers showed much variation in their ratings of support. The evaluations given by the three groups of listeners correlated strongly
FIGURE 4. Repetitive evaluation of support in the same samples replayed randomly during the listening test.
FIGURE 5. Estimation of support by Group C (N ⫽ 50). Mean values of each listener’s evaluations of support in all samples of supported singing (black dot) and unsupported singing (white dot). Lines up or down show SD (one direction only for clarity). The listeners have been arranged in order according to the amount of support they heard in the samples). Journal of Voice, Vol. 19, No. 2, 2005
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listener group. Likewise, they also heard less support in their own voice samples of unsupported singing (Figure 6). Although the average of the singers’ estimation of their colleagues’ supported voices was 56.1% support, the average of the singers’ estimations of their supported voice samples was 64.7% support. The difference was statistically significant (P ⱕ .01). The mean of the singers’ evaluation of their unsupported voice samples was 30.9% support, whereas the mean of the singers’ evaluation of their colleagues’ unsupported samples was 33.1% support. This difference was also statistically significant (P ⱕ .0001). Relationship between “good” and “supported” voice The evaluations of the three listener groups correlated strongly with each other for both perceived support (r ⫽ 0.81–0.85) and voice quality
FIGURE 6. The average degree of support in each singer’s (indicated by initials) samples evaluated by the singers (vertical axis) and by all singers (horizontal axis). Journal of Voice, Vol. 19, No. 2, 2005
(r ⫽ 0.79–0.85). Sum scores were thus computed for both perceived support and voice quality. The sums correlated very strongly with each other (r ⫽ 0.92); this indicates that they were almost identical. This suggests either that “supported voice” and “good voice” are more or less the same thing or that the judges could not hear the difference between the two. Acoustic and physiological correlates of good/supported voice Because the supported voice apparently was “a good voice,” the sum score “voice quality” was taken to be the dependent variable in further statistical analyses. The following results were obtained with genetic algorithm. Figure 7 illustrates the average relationships among subglottic pressure, EGG slope, spectrum parameters, and perceived voice quality, obtained with the genetic algorithm. Quality was evaluated as best when subglottic pressure was between 9.9 and 13.4 cm H2O. Voice quality, in turn, was evaluated as best when EGG slope was between 49⬚ and 63⬚. The relationships between perceived voice quality/ estimate of support and the values calculated from the spectra were dualistic. Voice quality was evaluated as best when the level difference between L1 and L0 was either between ⫺13.9 and ⫺4.7 dB or between ⫹4.3 and ⫹3.4 dB. Similarly, best voice quality seemed to be reached when the level difference between the singer’s formant region and L1 was either between ⫺30.5 and ⫺21.9 dB or between ⫺4.7 and ⫹3.8 dB. These two ranges for optimum result can be explained as reflecting different quality criteria for male and female voices and for different task types. The genetic algorithm shows the average tendencies more clearly. On the basis of mean results, however, it is not possible to draw any far-reaching conclusions. Figure 8 shows scatter plots between the evaluations of voice quality and the acoustic and physiological parameters for all samples. No correlations can be found when all samples from both men and women produced at different pitch and loudness levels are treated together. Therefore, correlation analyses were made for male and female voices and for different task types separately (Table 2).
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FIGURE 7. Relations between perceived voice quality and acoustic/physiological variables as obtained with the genetic algorithm. Ps ⫽ subglottic (oral) pressure, EGG slope ⫽ steepness of the closing phase of the electroglottographic signal, L1-L0 ⫽ level difference between the strongest peak in average spectrum and the fundamental frequency variation range, and Ls-L0 ⫽ level difference between the singer’s formant region (between 2 kHz and 3 kHz) and the fundamental frequency variation range.
In Table 2, a positive correlation existed between Ps (oral) and voice quality in intensity variation (pp-ff-pp) for women at both pitches and for men at high pitch. For the men, in intensity variation at low
pitch, the relation between Ps and voice quality was polynomial, which suggests that the best voice quality was reached when Ps obtained intermediate values. The relationship between EGG slope and Journal of Voice, Vol. 19, No. 2, 2005
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FIGURE 8. Scattergrams of perceived voice quality and acoustic/physiological variables. Ps ⫽ subglottic (oral) pressure, EGG slope ⫽ steepness of the closing phase of the electroglottographic signal, L1-L0 ⫽ level difference between the strongest peak in average spectrum and the fundamental frequency variation range, and Ls-L0 ⫽ level difference between the singer’s formant region (between 2 kHz and 3 kHz) and the fundamental frequency variation range.
voice quality also was polynomial for both men and women in intensity variation at low pitch and in sustained phonation at high pitch in male singers. For women, in intensity variation at high pitch, the EGG slope correlated positively with voice quality. For women, the level differences L1-L0 and Ls-L1 correlated negatively with perceived voice quality. In male singers, both correlations were positive at high pitch in sustained phonation, but only L1-L0 correlated significantly with voice quality in pp-ffpp variation. These findings suggest that a steeper spectral slope (relatively weaker L1 and Ls and/ or stronger fundamental) was regarded as positive in the female singers, but the opposite was true for the male singers. Journal of Voice, Vol. 19, No. 2, 2005
To find more precise acoustic/physiological correlates of quality, samples with the highest and the lowest percentage of support (best and poorest voice quality) were compared in each task and for men and women separately. Table 3 shows the average results and the significance of differences (t test) in the parameters. Ps varied between 6 and 13 cm H2O in the best samples of the female singers in this material, EGG slope between 44⬚ and 54⬚, L1-L0 between ⫺4 and ⫺8 dB, and Ls-L0 between ⫺18 and ⫺22 dB. For the men, the variation for the best samples was Ps 5–10 cm H2O, EGG slope 37⬚ to 54⬚, L1-L0 ⫹8 to ⫹14 dB, and Ls-L0 ⫺9 to ⫹2 dB. In the female singers’ samples with the lowest percentage of support, Ps was lower, EGG
SUPPORT IN SINGING TABLE 2. Correlations (Spearman; * ⫽ polynomial, order 2) Between Perceived Voice Quality and Acoustic Parameters for Male and Female Subjects in Various Tasks (number of samples 40 for females, 24 for males) FEMALES (N ⴝ 5)
MALES (N ⴝ 3)
(1) Sustained phonation Ps EGG slope L1-L0 Ls-L0
Low NS NS ⫺0.64 P ⫽ 0.001 ⫺0.61 P ⫽ .002
High NS NS ⫺0.61 P ⫽ 0.004 ⫺0.46 P ⫽ .04
Low NS NS NS
Low 0.82 P ⫽ .000 0.61* P ⫽ .029 ⫺0.66 P ⫽ .001 ⫺0.62 P ⫽ .002
High 0.55* P ⫽ .033 0.65 P ⫽ .004 ⫺0.50 P ⫽ .018 ⫺0.43 P ⫽ .044
Low 0.77* P ⫽ .011 0.86* P = .001 NS
NS
High NS 0.67* 0.64 P ⫽ .006 0.60 P ⫽ .012
(2) pp-ff-pp Ps EGG slope L1-L0 Ls-L0
NS
High 0.56 P ⫽ .046 NS 0.96 P ⫽ .000 NS
Low/high ⫽ pitch below/above the first register transition. Ps ⫽ subglottic (oral) pressure. EGG slope: L1-L0 ⫽ level difference between the strongest peak in average spectrum and the fundamental frequency variation range. Ls-L0 ⫽ level difference between singer’s formant region (between 2 kHz and 3 kHz) and the fundamental frequency variation range.
slope was higher at low pitch and lower at high pitch, and both L1-L0 and Ls-L0 were smaller. In the men, the poorest samples had higher Ps and EGG slope at low pitch and lower at high pitch; both L1L0 and Ls-L0 were smaller. In general, even in the best samples, the mean evaluation of support varied between 50.9% and 68.2% for the women and between 35.2% and 47.4% for the men. Figure 9 illustrates the spectral differences between the best male and female voices in the material. L0 is clearly weaker compared with L1 in the good male voice, whereas the opposite can be seen in the female voice. Ls is stronger in relation to L0 in the male voice than in the female voice. DISCUSSION Singers often seem to have very strong opinions about support in singing. However, these opinions
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are often quite different. Although, for example, Domingo claims he has obtained the finest control over his voice through support, Stampa rejects the concept “support” as harmful for the voice.3 The reason for these discrepancies may lie in terminological differences. In this study, the singers were assumed to know themselves, when they are singing with and without support. Interestingly, three of the seven subjects could not auditively distinguish between their samples produced with and without support. These samples also caused difficulties to other listeners. In general, listeners often disagreed on various samples: The same sample could be evaluated as representing almost no support at all and 100% of support. One singing pedagogue could not hear any really supported voice among the test samples. In spite of disagreements for various samples, the statistical treatment showed certain clear tendencies among the listeners’ evaluations. In the average, the listeners were by first impression able to differentiate between supported and unsupported voice samples. On the other hand, voice quality and support could not be distinguished in the listening evaluations. Thus, from the listener’s point of view, “supported voice” seems to be nothing but “good voice.” It seems to be a subjective choice, then, whether a person calls a good voice also a supported voice. “Good” should not be considered equivalent to “beautiful” because that, in turn, is much more a matter of subjective taste. The procedure of this study might have affected the results. When the subjects sang “with support,” they most likely sang as well as they possibly could, whereas when mimicking singing “without support,” it is possible that they just tried to sing less well. On the other hand, these professional singers were also song pedagogues, and it seems plausible that they can mimic different characteristics in singing. It is likely that, for some singers, “support” is an important tool for producing a good voice quality, whereas for others, “support” evokes images that might have a harmful effect on effortless phonation. Earlier studies9,10 on the differences between supported and unsupported singing have suggested that supported singing is, for example, characterized by a longer maximum phonation time, lower vertical laryngeal position (at least in men), higher subglottic Journal of Voice, Vol. 19, No. 2, 2005
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A. SONNINEN ET AL TABLE 3. Differences (Mean, SD in Parentheses) Between the Samples With Best and Poorest Voice Quality (Highest/Lowest % of Support) in Each Task
Females (N 5) (1) Sustained phonation Low Good Poor Sign. High Good Poor Sign. (2) pp-ff-pp Low Good Poor Sign. High Good Poor Sign. Males (N 3) (1) Sustained phonation Low Good Poor Sign. High Good Poor Sign. (2) pp-ff-pp Low Good Poor Sign. High Good Poor Sign.
Ps (cm H20)
EGG slope (⬚)
L1-L0 (dB)
Ls-L0 (dB)
Support (%)
8.6 (6.2) 7.0 (2.2) NS 5.7 (1.7) 6.3 (2.2) NS
52.1 (14.9) 60.7 (17.6) NS 48.1 (13.5) 40.0 (17.4) NS
⫺7.7 (4.0) 7.4 (4.4) P ⴝ .000 ⫺8.5 (8.4) 10.0 (7.1) P ⴝ .006
⫺22.2 (3.9) ⫺5.6 (10.8) P ⴝ .012 ⫺20.1 (6.7) ⫺3.3 (9.4) P ⴝ .012
67.5 (1.6) 18.5 (9.4) P ⴝ .000 50.9 (4.0) 11.0 (3.2) P ⴝ .000
13.0 (1.5) 5.4 (2.2) P ⴝ .000 9.1 (1.3) 5.2 (1.0) P ⴝ .001
43.9 (11.2) 53.3 (21.0) NS 54.0 (5.8) 30.8 (8.7) P ⴝ .001
⫺4.0 (7.3) 8.1 (4.5) P ⴝ .013 ⫺8.1 (8.0) 2.4 (2.3) P ⴝ .023
⫺17.6 (4.3) ⫺4.6 (4.8) P ⴝ .002 ⫺20.8 (0.9) ⫺10.5 (2.3) P ⴝ .000
68.2 (5.5) 34.3 (3.5) P ⴝ .000 57.3 (9.8) 9.1 (2.5) P ⴝ .000
9.7 (5.2) 11.2 (4.3) NS 5.0 (1.2) 4.4 (0.9) NS
53.9 (18.2) 45.4 (14.8) NS 50.0 (0.6) 31.3 (16.7) P ⴝ .035
13.7 (3.8) ⫺7.8 (14.8) P ⴝ .014 12.9 (1.2) ⫺1.9 (3.2) P ⴝ .000
⫺1.4 (2.4) ⫺17.5 (10.1) P ⴝ .008 ⫺6.6 (3.6) ⫺15.7 (2.0) P ⴝ .001
41.4 (6.2) 22.3 (5.4) P ⴝ .001 35.2 (6.2) 14.0(4.4) P ⴝ .000
9.7 (1.5) 13.0 (2.5) P ⴝ .036 7.5 (2.5) 4.3 (2.2) NS
36.7 (18.3) 58.7 (12.8) NS 37.0 (2.2) 30.3 (18.5) NS
14.1 (3.4) 5.4 (10.9) NS 8.5 (3.2) ⫺1.1 (3.3) P ⴝ .002
2.0 (2.1) ⫺3.7 (11.9) NS ⫺8.7 (6.5) ⫺8.4 (4.2) NS
47.4 (9.4) 25.7 (3.1) P ⴝ .001 40.2 (11.8) 11.3 (3.4) P ⴝ .001
Sign. ⫽ significance of difference, obtained with Student’s unpaired t test. Low/high ⫽ pitch below/above the first register transition. Ps ⫽ subglottic (oral) pressure. EGG slope ⫽ steepness of the closing phase (decreasing impedance). L1-L0 ⫽ level difference between the strongest peak in average spectrum and the fundamental frequency variation range. Ls-L0 ⫽ level difference between singer’s formant region (between 2 kHz and 3 kHz) and the fundamental frequency variation range.
pressure, higher peak airflow, higher glottal closing speed, and a less steep spectral slope than unsupported singing. The results of this study, in turn, suggest that the difference between supported and unsupported voice—that is, the difference between good and poor voice quality—is not categorically dualistic, but it is gender and task dependent. In some tasks, Ps was higher in good/supported voice, but in others either no significant correlation existed between Ps and perceived support or the relationship was polynomial; this suggests that the optimum would be reached at intermediate subglottic pressure values. The results were similar for EGG slope, which Journal of Voice, Vol. 19, No. 2, 2005
reflects glottal closing speed. As could be expected, the ideal spectrum slope was different for male and female singing and for different singing tasks. In general, a steeper slope (lower values for L1-L0 difference, ie, a weaker L1 or a stronger L0, and higher absolute values for the Ls-L0 difference, ie, a weaker Ls) was related to better voice quality in female singing, whereas the opposite was observed in male singing, especially at high pitch. Vennard8 defined support as a good control of subglottic pressure. According to Hirano,18 subglottic pressure varies approximately between 2 cm H2O and 50 cm H2O in singing, depending on the singing
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FIGURE 9. Long-term average spectrum of the samples that were evaluated as having most support.
style and the method used by the researcher for measurement. Subglottic pressure is lower in piano (about 5 cm H2O) than in forte (about 20 cm H2O). Subglottic pressure also generally rises with pitch. In our study, subglottic pressure varied between 5 and 13 cm H2O in the samples that were perceived as best in quality. Samples with the poorest quality obtained higher or lower mean Ps values, which does not mean that in all good singing, Psub should be in that range. Instead, the results suggest that, although Psub naturally varies according to pitch and loudness, from the point of view of perception, the
best samples these subjects produced in this study had intermediate Psub values, which in these tests happened to be in that range. Most likely, this result reflects the type of voice production. Deviation from the optimum toward higher subglottic pressure values may be related to a shift from flow phonation to pressed phonation, whereas lower-than-optimum pressure values may be obtained in breathy, hypofunctional voice production.16,18 Although the absolute values for the “optimum” glottal closing speed naturally vary depending on gender, pitch, intensity, register, voice category, and Journal of Voice, Vol. 19, No. 2, 2005
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so on, the polynomial relation between EGG slope and perceived voice quality seems to suggest a relative optimum in glottal closing speed. This is in line with the observations of Verdolini et al19 on “resonant voice.” Because subglottic pressure needs to vary according to pitch and loudness, the optimal glottal closing speed cannot be just a result of certain subglottic pressure. Instead, optimal glottal closing speed requires glottal adjustment, which may belong to the concept of “support” in light of the results from this study. These adjustments could consist of optimal prephonatory size of the glottis and optimal stiffness of the vocal folds: because the prephonatory size of the glottis is small, as it is in pressed phonation, the glottal closing speed is higher than normal, and in contrast, when the size of the glottis is relatively large, the voice production is asthenic, and the relative glottal closing speed is low. Furthermore, in the falsetto register, the relative vocalis activity is lower,20 and therefore, the membranous portion of the vocal folds, the cover, is stiff. Thus, the relative glottal closing speed is lower than in modal register, in which the cover is lax and pliable. The vibratory mode of the vocal folds also determines the spectral characteristics of the voice: Spectral slope becomes less steep as the glottal closing speed increases and vice versa.14 Steeper spectral slope in female voices suggests a more falsetto type of phonation. In high pitches, it may also reflect formant tuning, ie, a coincidence of the fundamental and the first formant, which boosts L1 considerably.16,21 In male voices, a less steep slope (stronger L1 and Ls) suggests both a more chest register type of phonation (with stronger harmonics per se) and resonance effects: Raising F1 higher than the fundamental and tuning it to an overtone (or tuning of the second formant to an overtone) boosts L1 (or L2, ie, the level of the second formant region) and may help to keep the voice masculine even at high pitches,22 whereas a strong singer’s formant is needed to obtain a desirable ringing quality and a sufficient audibility in the male voice. If support means control of subglottic pressure, it must in practice mean a constantly varying active cooperation between various muscles. Subglottic pressure varies according to lung volume, tending to be high when lung volume is high (after deep inspiration) and low when lung volume is low (after Journal of Voice, Vol. 19, No. 2, 2005
long/forceful expiration). To keep subglottic pressure constant when needed for a certain pitch and loudness, these lung-volume related pressure changes need the compensation of the inspiratory muscles at the beginning of the phrase and the expiratory muscles at the end of the phrase (Figure 10). The function of respiratory muscles in the control of subglottic pressure is different in forte than in piano singing. “Rib reserve”24 can be used by the singer without compensation of inspiratory muscles at the beginning of forte phonation. Function of the expiratory muscles is needed more in forte than in piano singing. So the contraction of the respiratory muscles in singing cannot be static. As the results of Nadoleczny6 and Schilling7 in the beginning of the 20th century and the recent results of Thomasson and Sundberg25 show, singers use different breathing patterns. This means that the goal, control of subglottic pressure, can be achieved in different ways. For a simplified analogy, in playing the accordion, the sound can be produced in three ways: (1) by pressing the bellows with both hands, (2) by pressing the bellows with the left hand while keeping the right hand still, or (3) by pressing the bellows with the right hand while keeping the left one still. Most likely, the pressure control can be performed more accurately in the second and third ways when the passive part (hand still) gives support and helps in concentrating on the function of the active part in the “controlling system.” In voice production, three basic alternatives are offered to control subglottic pressure: (1) both the abdominal and thoracic muscles are active, (2) abdominal muscles are active and thoracic muscles are more or less passive, or (3) thoracic muscles are active and abdominal muscles are more passive. Both abdominal and thoracic muscles can be involved in the control of subglottic pressure when needed (Figure 9). In 13 of the 30 singers interviewed by Hines,3 the description of support in singing seems to agree well with the concept of thoracic support by Schilling.7 There, “the chest maintains the inspiratory position for a longer time, while the diaphragm ascends gradually.” On the other hand, obviously singers using diaphragmatic support exist, in which “the diaphragm maintains its inspiratory descended position for a longer period of phonic expiration (up to 8 seconds). At the same time, the elevated chest
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FIGURE 10. Control of subglottic pressure through cooperation between inspiratory (arrows to the left) and expiratory (arrows to the right) muscle activity. Figure adapted from Draper et al.23
descends slowly, liberating the respiratory energy, which was accumulated through maximal inspiration, by pectoral expiration.”7 Singers typically have strong ideas of their breathing pattern, but the results
of Watson and Hixon26 have shown that the ideas are not necessarily related to objectively measurable events. However, the results obtained by Thomasson and Sundberg25 suggest that singers are consistent Journal of Voice, Vol. 19, No. 2, 2005
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in their breathing patterns; ie, they repeatedly use the same pattern for the same singing tasks. Type of breathing is related to the vertical position of the larynx and to phonation type. As the diaphragm descends, the larynx is also pulled down.27,28 This, in turn, poses an abductory tendency on the glottis. Control of the diaphragm is related to flow phonation, characterized by a relatively large glottal airflow.28 Furthermore, phonation at a larger lung volume is related to a lower position of the larynx and flow phonation.29 Type of breathing per se does not necessarily determine the type of support exploited. However, the so-called costo-abdominal breathing in which the diaphragm descends and the rib cage expands during inspiration offers the best possibilities to choose between types of support. The choice, in turn, may even be related to the singer’s body type. Subglottic pressure, the driving force of the vocal fold vibration, is determined not only by respiratory activity but also by the combination of respiratory and glottal factors. Thus, support should be a dynamic phenomenon requiring varying and correctly timed, well-coordinated contraction of respiratory and phonatory muscles to control subglottic pressure adequately. The sensation “press-counterpress, one in balance against the other” reported by some singers (eg, Crespin in Hines3) could be related to this coordination. The inertia of the air column of the vocal tract, which can be controlled by widening and narrowing the vocal tract, might also play a role in the delicate control of voice production during singing and contribute to the singers’ subjective sensations of support. CONCLUSIONS 1. It is possible to differentiate between supported and unsupported voice samples by impression. 2. Trained singers and nonsingers did not differ significantly in their abilities to evaluate support. 3. Singers evaluated their samples of supported singing as having more support than did the other listeners, and similarly, the singers heard less support in their samples of unsupported singing. Journal of Voice, Vol. 19, No. 2, 2005
4. From the point of view of perception, “supported voice” was the same as “good voice.” 5. The results suggest that although the absolute values for Ps and EGG slope may be gender and task dependent, best voice quality is characterized by intermediate Ps and EGG slope values and, thus, neither pressed nor breathy phonation. Good voice quality in female singing requires a sufficiently steep spectral slope, whereas, in male singing, a less steep spectrum slope is appreciated.
Acknowledgments: The authors thank the subjects and the listening panel. Mr. Timo Honkonen, singing pedagogue, and Professor Paavo Malinen, expert in mathematics, are also thanked for fruitful discussions.
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