Vibrato Changes Following Imagery *Lynda Moorcroft, †Dianna T. Kenny, and ‡Jennifer Oates, *ySydney, New South Wales, and zMelbourne, Victoria, Australia Summary: Objectives. This study investigated acoustic change in singers’ vibrato following imagery and nonimagery tasks. Study Design. The study used a fully randomized cross-over (six conditions 3 two times) block design, in which each singer received each intervention in random order. Data were analyzed using the general linear model (GLM). Main effects for time and condition and interaction effects (time 3 condition) were calculated for each dependent measure. Methods. Six classically trained female singers recorded an 8-bar solo before and after three nonvocal, 25 minute tasks. Each singer performed the tasks in a different randomized order in a single sitting. Task 1 involved imagery of the breath directed up and down as far from the larynx as possible; Task 2 used Braille music code, enabling the singer to engage in tactile, kinesthetic and visual imagery related to music but unrelated to breath function; Task 3 was a nonimagery activity requiring the completion of a cloze passage about breath function. From the 11 longest notes in each solo, spectrograms of the partials were produced and assessed for pre- to post-test changes in vibrato rate, vibrato extent, and sound pressure level (SPL). Results. Only the breathing imagery task produced significantly more moderate and regular vibrato rates. Vibrato extent was not responsive to any intervention. Conclusions. Findings indicate that breathing imagery regulates singers’ vibrato in a manner consistent with that of a more proficient, warmed-up voice. Key Words: Breathing–Imagery–Vibrato–Warm-up–Tone quality–Classical female singers. INTRODUCTION Singers trained in the Western classical tradition often use indirect techniques as an aid to soliciting the complex and often subconscious physiological coordinations that produce optimal vocal results. Mental imagery is one such technique, and indeed ‘‘the discipline of singing and vocal pedagogy . has consistently and historically used mental imaging techniques to achieve its objectives.’’ (p. 41)1 Although Cleveland1 noted the need to extend voice research into the science of mental imagery, his call has largely been ignored to date. Imagery used by singers often draws on the aural, visual, and proprioceptive senses.2–4 It may or may not be text-based or represent some aspect of physiology. However, because ‘‘sensation in the larynx means lack of freedom in the larynx,’’ (p. 154)5 and the voice tends to be more artistically acceptable if it feels to the user as although it were produced in almost any other region of the body than the throat,3,6–9 much of the imagery traditionally practiced as an aid to technical control focuses the vocalist’s attention away from the throat in a manner that does not represent reality. Such images have played an important role in voice teaching for at least five centuries10 and include those in which sensations of the breath or the tone are directed far from the larynx and even to some point outside the body.10,11
Accepted for publication May 7, 2014. From the *Australian Centre for Applied Research in Music Performance, The University of Sydney, Sydney, New South Wales, Australia; yFaculty of Arts and Social Sciences, The University of Sydney, Sydney, New South Wales, Australia; and the zFaculty of Health Sciences, La Trobe University, Melbourne, Victoria, Australia. Address correspondence and reprint requests to Dianna T. Kenny, The University of Sydney, Room 404, Building J12, Cleveland St, Chippendale, NSW 2006, Australia. E-mail: [email protected] Journal of Voice, Vol. 29, No. 2, pp. 182-190 0892-1997/$36.00 Ó 2015 The Voice Foundation http://dx.doi.org/10.1016/j.jvoice.2014.06.002
Imagery of the breath upholds the teachings of the Italian school of singing, that ‘‘the focus of the tone (the placement) and the control of the breath are considered to be one action.’’ (p. 80)12 That is, the bodily sensations the singer focuses on remain the same regardless of whether the singer is breathing in or singing out.12 Giovanni Battista Lamperti taught: ‘‘The desire to feel the ‘touch’ of the ‘point’ of tone, becomes the objective guide to the breath’’ (p. 70)13— a maxim sometimes paraphrased as ‘‘Breathe where you sing. Sing where you breathe.’’ (p. 10)14 However, vocal training is generally required to apply such a concept to advantage. The singer with an inefficient, poor quality voice senses the voice solely at vocal fold level,15 whereas the accomplished singer’s perception of a resonant voice involves sensations throughout the body.6,16 Baritone Thomas Quasthoff reports: ‘‘It is very important to feel the breathing inside your entire body, and not only in a separated part of your body. The whole human being is the instrument, not only the larynx.’’ (p. 264)17 To aid the perception of sensations associated with an accomplished resonant voice, singers are sometimes presented with imagery such as that in Figure 1 drawn by the singer and teacher Richard Br€unner.6 Figure 1 shows a typical beginner singer on the left, who is aware of breathing only in the throat and the chest, and a more accomplished singer on the right, who imagines the breath being taken much deeper into the torso and up to the top of the head. Extending this concept, the sensations of the breath or the tone are sometimes imagined projecting beyond the head and torso. The singer Lilli Lehmann18 wrote of the need to always have an inner picture of the stream of breath that directs the highest notes to a place above the head as though shooting into the air. To counterbalance upward sensations, singers may also use downward-directed images of the breath going to the pelvic floor, the knees, the soles of the feet, or into roots
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FIGURE 1. Imagery to aid perception of sensations. (Br€unner R. Gesangstechnik. Regensburg: Feuchtinger and Gleichauf; 1993:p. 90. Reprinted with permission). below the stage floor. Br€ unner6 writes that a good singer strikes broad, deep roots ‘‘into the earth’’ (p. 24) . ‘‘like a powerful tree’’ (p. 91). In reality, the breath or the voice cannot be directed to some focal point or points of sensation as the images suggest. Consequently, not all singing authorities support the use of such imagery.19 Yet, the vocal coach, Sergius Kagen, although decrying images which ‘‘put to shame the most fantasticallyminded surrealist poet,’’ (p. 82)20 nevertheless concedes that particularly gifted singers appear to respond to them. What the singing literature significantly fails to note is that the practice of such imagery is not restricted to the discipline of singing. Similar imagery has a long history of use in Eastern meditation and in Chinese traditional healing21 where the ability to focus the mind, for example on the breath, serves to calm anxiety and assist with the body’s stress related responses. More recently, it has been documented in the practice of Western physiotherapy21,22 and performance disciplines other than singing.23–28 As reported by a professional dancer: ‘‘Sometimes when you’re learning a new skill, you become bogged down by the physics of the movement. And sometimes it takes someone to say to you ‘try and just let the air come out of the top of your head’. And suddenly you’re not so much worried about your foot but you’re focusing on some other part of your body, and that will just allow the leg to do what it needs to do.’’ (p. 407)28
It has been suggested that breathing imagery serves not only as a distraction from negative self-talk, but also improves spinal alignment6,27,29 and diaphragmatic breathing,6,21 which in turn assists with the management of stress and relaxation levels,21 panic attacks and performance anxiety.23,30,31 Although the vocal literature is generally devoid of references to performance anxiety management, it does suggests that such imagery may assist with balancing the upward and downward forces in the stylopharyngeal muscle complex,32 that it raises the soft palate, lowers the larynx,8,9,33 and maintains larynx stability.34 These actions are linked to the freeing of laryngeal constriction, obtaining an ‘‘open throat’’9,33,34 and improved tone quality.8,12 However, for singers the freeing of laryngeal constriction is linked to the elimination of one of the most
183 detrimental symptoms of performance anxiety — the word ‘‘anxiety’’ stemming from Greek and Latin words meaning ‘‘constriction’’, ‘‘pressing tight’’ and ‘‘strangling.’’35 The literature for the spoken voice adds that if breathing imagery is used pre-performance, it serves as a silent warm-up by creating a mental blueprint for the sound.24,25 Adding credence to the theory of a mental blueprint, the discovery of the mirror neuron system supports claims that imagery activates neural responses, triggering physical adjustments that are often beyond conscious control.36,37 Furthermore, mirror neurons show greater activation the more the individual has a strong sense of the goal to be achieved38,39; and pedagogical wisdom suggests imagery of sensations directed both upward and downward, far from the larynx, presents the singer with a proprioceptive goal linked to skilled performance and optimal vocal tone quality. Thus, Hurley40 proposes that the presence of mirror neurons may account for why musicians often report that imagining a skilled performance in music improves performance. In the tradition of Western classical singing, skilled performance requires optimal vocal tone which possesses as much brilliance and mellowness as possible.8 Vennard writes that the singer’s sensations which appear to be directed up and forward are related to a bright brilliance of tone and those directed down and back are related to a darker mellowness of tone, and for a ‘‘chiaroscuro’’ ideal balance of brilliance and mellowness, both of these directionally opposing sensations must occur simultaneously.8 Thus, according to Vennard, if imagery is used optimally then vocal tone quality improves. This suggests that breathing imagery may affect singers’ vibrato, because it has long been observed that vocal color is determined above all by vibrato,41 and that the faster or slower the vibrato, the brighter or darker the tone.12 Furthermore, in music where a ‘‘chiaroscuro’’ beauty of tone is of primary importance, the more highly trained and skilled the singer, the more moderate and regular the vibrato rate.42–46 Excessively fast and unstable vibrato rates are often found in students at the commencement of vocal training,46,47 but are also typical acoustic indicators of muscular hyperactivity that occur in situations of high stress, excessive force, and performance anxiety, irrespective of singer level.5,8,48,49 In addition to producing a very bright, sometimes shrill quality, fast vibrato rates in the 6–8 cycles/second range may sound like a bleat,48 with those in the 7 or 8 cycles/second range associated with tremolo.32 Slow vibrato is typical where lethargy or poor muscle tone is present.5,46 Generally, vibrato rates below 5 cycles/second are considered unacceptably slow,45 produce a particularly dark tone quality, and tend toward a wobble.50 Vibrato near 4 cycles/second clearly undulates rather than creating the impression of a constant pitch.45,48 An acceptable tone color may vary depending on the repertoire, and so too may the vibrato rate. Exceptionally fast and exceptionally slow vibrato rates appear to be important when particularly intense emotions or extreme psychological states are portrayed.48,49 For example, Maria Callas has recorded vibrato rates as fast as 7.1 cycles/second in the mad scene from Donizetti’s opera ‘‘Lucia di Lammermoor,’’51 where the
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character has just murdered her bridegroom, and vibrato rates as slow as 4.1 cycles/second in the sleep-walking scene from Verdi’s opera ‘‘Macbeth,’’52 where the singer is portraying overwhelming emotional disintegration.53 Under more usual circumstances, a rate of 7.1 cycles/second is considered excessively fast,48 and 4.1 cycles/second is unacceptably slow.52 Titze suggests that Pavarotti’s average vibrato rate of 5.5 cycles/second represents a vibrato speed that audiences today find particularly appealing, as it is neither too fast nor too slow. This is in accord with M€ urbe et al47 who classified vibrato below 5.2 cycles/second as slow, and vibrato above 5.8 cycles/ second as fast, and who also found that after 3 years’ tertiary level vocal training, singers were more likely to produce moderate vibrato rates within the range of 5.2–5.8 cycles/second. It is also in accord with the finding that after vocal warm-up there is a tendency for vibrato to draw closer to the region of 5.5 cycles/second.54,55 Thus, with vibrato linked to warming up, to tone color, and to stress and relaxation, and with breathing imagery claiming similar links, the following research questions were posed for the present study. 1. What is the acoustic effect of breathing imagery on singers’ vibrato? 2. Do any changes observed resemble those generally associated with a vocal warm-up?
METHOD Singer background Six classically trained female singers, each from a different studio, participated. Three were studying tertiary level singing, and three had completed tertiary studies and sang professionally (mean age ¼ 29 years, SD ¼ 7 years; mean years of vocal study ¼ 13, SD ¼ 5 years). Singer profiles are presented in Table 1. The use of only female singers prevented genderrelated variables entering into the vibrato analysis. The vocal solo All singers were asked to learn 8 bars from Villa-Lobos’ ‘‘Bachianas Brasileiras No 5 Aria.’’ The vocal range spanned a major
10th from D4 (294 Hz) to F#5 (740 Hz). The excerpt called for a calm, lyrical delivery and considerable vocal beauty for effective performance. The composer required this section to be sung solely on an ‘‘ah.’’ The singers were given the print music, a recording of the accompaniment to be used, and requested not to warm-up on the recording day. It was considered that if the singer had already vocally warmed up such that they were singing their best before the recording session, then perhaps only if an intervention had a detrimental effect on the voice could a change in vocal performance be noted. Recording procedure All singers had individual appointments to record their voices. They were fitted with an AKG C-477 miniature condenser omnidirectional microphone (AKG Acoustics, Vienna, Austria) which was head-mounted so as to maintain a constant distance of 7 cm from the corner of the mouth to the microphone. The microphone was connected to a DAT Marantz compact disc recorder model CDR-640 (Marantz Japan Inc., Kanagawa, Japan) via a Behringer Ultragain Pro MIC-2200 preamplifier (Behringer International, Willich, Germany). Singers were also fitted with Beyerdynamic DT331 free-field earphones (Beyerdynamic GmbH & Co. KG, Heilbronn, Germany) through which to hear the pre-recorded accompaniment. This enabled the voice to be recorded without the accompaniment. It also ensured that all singers maintained an identical tempo, which was necessary as vibrato rate may be influenced by note duration.50 The recording level of the voice was first checked while the singer sang once through the excerpt. As fluctuations in the level of performance stress may influence vibrato characteristics, this process also served to allay singer unfamiliarity with performance conditions. The singers then recorded the excerpt before and after three non-vocal 25 minute tasks. Each singer performed the tasks in a different, randomized order. One task involved imagery of the breath directed up and down as far from the larynx as possible. Another task used Braille music code, which enabled the singer to engage in tactile, kinesthetic and visual imagery related to music but unrelated to breath function. A third task was a non-imagery activity in which the singer completed a cloze passage about breath function. So that all tasks might be perceived as equally valid, the singers
TABLE 1. Singer Profiles SingerSubject
Age (y)
Years of Vocal Study
Vocal Education
Performance Background
1 2 3
19 24 25
7 9 9
Bachelor of Music 1st year Bachelor of Music 2nd year Bachelor of Music 3rd year
4
27
12
Bachelor of Music (Honors)
5 6
49 29
26 16
Diploma of Operatic Art Bachelor of Music; Diploma of Opera
Student examinations Student recitals Student recitals, semi-professional engagements at municipal level Winner of state-wide vocal competitions, state opera Young Artists training program State opera company chorus member, solo recitalist Winner of nation-wide vocal competition, state opera company soloist
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were told that the project was investigating the effect of varying levels of relaxation on the voice. At the completion of recording, singer Sound Pressure Level (SPL) was calibrated using two different dB readings of a 1000 Hz pure sine wave tone and a Rion Integrating Sound Level Meter model NL-06 (Rion Co. Ltd, Tokyo, Japan). For a full account of each intervention see Moorcroft.54 Acoustic analysis All vocal samples were converted into graphic form using the computer software programs Phog Interactive Phonetography System Version 2.0 (Hitech, Sweden) and Soundswell Core Analysis Version 4.0 (Hitech, Sweden). Spectrograms of the 11 sustained notes from each vocal solo (ie, 132 notes per intervention activity, 396 notes in total) were produced and each vibrato cycle assessed for rate and extent. The 11 notes assessed per solo are indicated in Figure 2. The screen resolution for each spectrogram was the result of settings providing the fast Fourier transform (FFT) size 1066/ 2048, frequency range to 5476 Hz, window length 33 ms and a Hanning Window with a bandwidth of 30 Hz. Each spectrogram displayed the undulations of the partials over the length of a selected note. These undulations which represented vibrato cycles were measured by selecting one of the clearly displayed high partials, manually placing a computer cursor over the peak and trough of each vibrato cycle in that partial and registering the corresponding time and frequency from the spectrogram onto a spreadsheet (Excel, Microsoft Office 2000, Redmond, WA). High partials were used, as resolution increases with the partial number.56 From the spreadsheet the registered frequencies were divided by the number of the partial to establish their related fundamental frequencies. To ascertain vibrato extent, the maximum departure from the average fundamental frequency was measured by taking each vibrato cycle, calculating the distance from peak to trough in semitones and dividing the result by two. Hertz were converted into semitones using the formula: 12 log10 ðF0 Þ log10 16:35 F0 in ST ¼ log10 2 Vibrato rate was measured from the time difference between adjacent vibrato peaks and expressed in cycles per second. For both vibrato rate and vibrato extent, the mean values and corresponding standard deviations were calculated for the following:
For the group of singers as a whole under each condition, For each solo under each condition, and For each of the 11 sustained notes in each solo. In addition, from the 11 mean vibrato rates per solo, the fastest, slowest and median values were selected to observe the range of vibrato rates for each solo and the average range of vibrato rates per condition. Changes in both vibrato rate and vibrato extent were also compared with SPL changes. SPL was measured in decibels and established from the graphic representation of an upper and a lower calibration tone recorded directly after each singer’s solos. Mean SPL was extracted from each solo using the Hitech Soundswell Core Analysis histogram function with a resolution setting of 512 bins. Acoustic data were subject to statistical analysis using SPSS (Statistical Package for the Social Sciences v 16; SPSS Inc, Chicago, IL). The design of the study was a fully randomized cross-over block design, in which each singer received each intervention in random order. Repeated measures multivariate analyses of variance were used to analyze the results. The study comprised a 6 3 2 design: (six dependent measures: mean vibrato rate, standard deviation, fastest vibrato rate, slowest vibrato rate, median vibrato rate, and the range of vibrato rates [ie, fastest minus slowest vibrato rate]) by time (before intervention and after intervention). Data were subjected to analysis using the general linear model (GLM). Main effects for time and condition and interaction effects (time 3 condition) were calculated for each dependent measure. A further set of analyzes were conducted to assess the effect of order of intervention on the outcome of the six dependent measures. The analysis was a single factor within subject repeated measures design, with the difference score for each dependent variable calculated by subtracting pretest from the posttest scores. All first, second, and third presentation difference scores were compared to assess possible order effects. The distributions for each dependent measure were assessed for normality and outliers. Examination of skewness and kurtosis statistics indicated that the distributions were relatively normally distributed. Mauchly’s test of sphericity was assessed before interpreting the F statistics from the GLM. Those variables with significance >0.05 were interpreted using the sphericity assumed statistics; those with significance 0.05 were interpreted using the Huynh-Feldt epsilon adjustment.
FIGURE 2. The 11 notes acoustically assessed for vibrato rate and vibrato extent.
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FIGURE 3. The mean and median vibrato rates for the solo, and the mean fastest and mean slowest vibrato rates from each singer’s 11 long held notes per solo. RESULTS Pre- to posttest vibrato rate changes for the group as a whole are presented in Figure 3. As indicated in Figure 3, after the breathing imagery, although no significant change occurred in the group mean (mean change ¼ 0.13, P ¼ 0.15) or median (mean change ¼ 0.06, P ¼ 0.47) vibrato rates, there was a significant reduction in the range of mean vibrato rates for the group (mean change ¼ 0.52, P ¼ 0.02). In contrast, after the Braille music imagery, there was a significant reduction in the group mean (mean change ¼ 0.17, P ¼ 0.01) and median (mean change ¼ 0.18, P ¼ 0.01) vibrato rates, and no significant reduction in the range of mean vibrato rates for the group (mean change ¼ 0.19, P ¼ 0.10). After the cloze passage on breathing, no significant changes were found in either the group mean (mean change ¼ 0.0, P ¼ 0.87) or median (mean change ¼ 0.03, P ¼ 0.38) vibrato rates, nor in the range of mean vibrato rates for the group (mean change ¼ 0.05, P ¼ 0.64). Each singer’s pre- and post-intervention mean vibrato rate is presented in Figure 4.
Breathing imagery 6.4 1
6.3
6.4 1
6.3
6.2
6.2
6.2
6.1
6.1
6.1
6.0
6.0
5.9
5.9
5.8 5.7 5.6
5 6
5.5 5.4 5.3
4
5.8 5.7
5.9
5
5.6 5.5 5.4 5.3
4 6
5.8
5.6
5.4
5.1
5.1
5.1
5.0
5.0
4.9
4.8
After
4
5.0
3
4.9
Before
6
5.3 5.2
4.8
5
5.5
5.2
3
2
5.7
5.2
4.9
1
6.0 2 Cycles per second
2
Cycles per second
Cycles per second
Cloze passage
Braille imagery
6.4 6.3
As indicated, the pre-intervention vibrato for the professional singers 4, 5, and 6 was consistently more moderate (ranging from 5.35–5.73 cycles/second) than that of the student singers who produced both faster (singers 1 and 2) and slower (singer 3) vibrato. However, after the breathing imagery, mean vibrato rates faster than 5.6 cycles/second became slower, and mean vibrato rates below 5.4 became faster. Even the professional singers’ mean vibrato rates compacted to between 5.42 and 5.58 cycles/second. By contrast, after the Braille music imagery, all singers produced slower mean vibrato rates for the solo. Singers with the fastest mean vibrato rates slowed the most. The non-imagery cloze passage produced the least change in mean vibrato rates for the solo. The results of the repeated measures Analysis of Variation (ANOVA), as reported in Table 2, show a significant pre- to post-test difference in vibrato rates for the breathing imagery and the Braille imagery, but not for the cloze passage. A significant pre- to post-test difference between the 11 notes assessed occurred only for the breathing imagery. Figure 5 illustrates the variation in vibrato rates when
3
4.8
Before
After
Before
FIGURE 4. Mean vibrato rates for each of the six singers, pre- and post-intervention.
After
Lynda Moorcroft, et al
TABLE 2. Results of the Repeated Measures ANOVA for Mean Vibrato Rates in Each Solo
Condition
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Vibrato Following Imagery
P Value for Change Over Time (Pre vs Post)
P Value for Differences Between 11 Notes
0.001
Accepted for publication May 7, 2014. From the *Australian Centre for Applied Research in Music Performance, The University of Sydney, Sydney, New South Wales, Australia; yFaculty of Arts and Social Sciences, The University of Sydney, Sydney, New South Wales, Australia; and the zFaculty of Health Sciences, La Trobe University, Melbourne, Victoria, Australia. Address correspondence and reprint requests to Dianna T. Kenny, The University of Sydney, Room 404, Building J12, Cleveland St, Chippendale, NSW 2006, Australia. E-mail: [email protected] Journal of Voice, Vol. 29, No. 2, pp. 182-190 0892-1997/$36.00 Ó 2015 The Voice Foundation http://dx.doi.org/10.1016/j.jvoice.2014.06.002
Imagery of the breath upholds the teachings of the Italian school of singing, that ‘‘the focus of the tone (the placement) and the control of the breath are considered to be one action.’’ (p. 80)12 That is, the bodily sensations the singer focuses on remain the same regardless of whether the singer is breathing in or singing out.12 Giovanni Battista Lamperti taught: ‘‘The desire to feel the ‘touch’ of the ‘point’ of tone, becomes the objective guide to the breath’’ (p. 70)13— a maxim sometimes paraphrased as ‘‘Breathe where you sing. Sing where you breathe.’’ (p. 10)14 However, vocal training is generally required to apply such a concept to advantage. The singer with an inefficient, poor quality voice senses the voice solely at vocal fold level,15 whereas the accomplished singer’s perception of a resonant voice involves sensations throughout the body.6,16 Baritone Thomas Quasthoff reports: ‘‘It is very important to feel the breathing inside your entire body, and not only in a separated part of your body. The whole human being is the instrument, not only the larynx.’’ (p. 264)17 To aid the perception of sensations associated with an accomplished resonant voice, singers are sometimes presented with imagery such as that in Figure 1 drawn by the singer and teacher Richard Br€unner.6 Figure 1 shows a typical beginner singer on the left, who is aware of breathing only in the throat and the chest, and a more accomplished singer on the right, who imagines the breath being taken much deeper into the torso and up to the top of the head. Extending this concept, the sensations of the breath or the tone are sometimes imagined projecting beyond the head and torso. The singer Lilli Lehmann18 wrote of the need to always have an inner picture of the stream of breath that directs the highest notes to a place above the head as though shooting into the air. To counterbalance upward sensations, singers may also use downward-directed images of the breath going to the pelvic floor, the knees, the soles of the feet, or into roots
Lynda Moorcroft, et al
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FIGURE 1. Imagery to aid perception of sensations. (Br€unner R. Gesangstechnik. Regensburg: Feuchtinger and Gleichauf; 1993:p. 90. Reprinted with permission). below the stage floor. Br€ unner6 writes that a good singer strikes broad, deep roots ‘‘into the earth’’ (p. 24) . ‘‘like a powerful tree’’ (p. 91). In reality, the breath or the voice cannot be directed to some focal point or points of sensation as the images suggest. Consequently, not all singing authorities support the use of such imagery.19 Yet, the vocal coach, Sergius Kagen, although decrying images which ‘‘put to shame the most fantasticallyminded surrealist poet,’’ (p. 82)20 nevertheless concedes that particularly gifted singers appear to respond to them. What the singing literature significantly fails to note is that the practice of such imagery is not restricted to the discipline of singing. Similar imagery has a long history of use in Eastern meditation and in Chinese traditional healing21 where the ability to focus the mind, for example on the breath, serves to calm anxiety and assist with the body’s stress related responses. More recently, it has been documented in the practice of Western physiotherapy21,22 and performance disciplines other than singing.23–28 As reported by a professional dancer: ‘‘Sometimes when you’re learning a new skill, you become bogged down by the physics of the movement. And sometimes it takes someone to say to you ‘try and just let the air come out of the top of your head’. And suddenly you’re not so much worried about your foot but you’re focusing on some other part of your body, and that will just allow the leg to do what it needs to do.’’ (p. 407)28
It has been suggested that breathing imagery serves not only as a distraction from negative self-talk, but also improves spinal alignment6,27,29 and diaphragmatic breathing,6,21 which in turn assists with the management of stress and relaxation levels,21 panic attacks and performance anxiety.23,30,31 Although the vocal literature is generally devoid of references to performance anxiety management, it does suggests that such imagery may assist with balancing the upward and downward forces in the stylopharyngeal muscle complex,32 that it raises the soft palate, lowers the larynx,8,9,33 and maintains larynx stability.34 These actions are linked to the freeing of laryngeal constriction, obtaining an ‘‘open throat’’9,33,34 and improved tone quality.8,12 However, for singers the freeing of laryngeal constriction is linked to the elimination of one of the most
183 detrimental symptoms of performance anxiety — the word ‘‘anxiety’’ stemming from Greek and Latin words meaning ‘‘constriction’’, ‘‘pressing tight’’ and ‘‘strangling.’’35 The literature for the spoken voice adds that if breathing imagery is used pre-performance, it serves as a silent warm-up by creating a mental blueprint for the sound.24,25 Adding credence to the theory of a mental blueprint, the discovery of the mirror neuron system supports claims that imagery activates neural responses, triggering physical adjustments that are often beyond conscious control.36,37 Furthermore, mirror neurons show greater activation the more the individual has a strong sense of the goal to be achieved38,39; and pedagogical wisdom suggests imagery of sensations directed both upward and downward, far from the larynx, presents the singer with a proprioceptive goal linked to skilled performance and optimal vocal tone quality. Thus, Hurley40 proposes that the presence of mirror neurons may account for why musicians often report that imagining a skilled performance in music improves performance. In the tradition of Western classical singing, skilled performance requires optimal vocal tone which possesses as much brilliance and mellowness as possible.8 Vennard writes that the singer’s sensations which appear to be directed up and forward are related to a bright brilliance of tone and those directed down and back are related to a darker mellowness of tone, and for a ‘‘chiaroscuro’’ ideal balance of brilliance and mellowness, both of these directionally opposing sensations must occur simultaneously.8 Thus, according to Vennard, if imagery is used optimally then vocal tone quality improves. This suggests that breathing imagery may affect singers’ vibrato, because it has long been observed that vocal color is determined above all by vibrato,41 and that the faster or slower the vibrato, the brighter or darker the tone.12 Furthermore, in music where a ‘‘chiaroscuro’’ beauty of tone is of primary importance, the more highly trained and skilled the singer, the more moderate and regular the vibrato rate.42–46 Excessively fast and unstable vibrato rates are often found in students at the commencement of vocal training,46,47 but are also typical acoustic indicators of muscular hyperactivity that occur in situations of high stress, excessive force, and performance anxiety, irrespective of singer level.5,8,48,49 In addition to producing a very bright, sometimes shrill quality, fast vibrato rates in the 6–8 cycles/second range may sound like a bleat,48 with those in the 7 or 8 cycles/second range associated with tremolo.32 Slow vibrato is typical where lethargy or poor muscle tone is present.5,46 Generally, vibrato rates below 5 cycles/second are considered unacceptably slow,45 produce a particularly dark tone quality, and tend toward a wobble.50 Vibrato near 4 cycles/second clearly undulates rather than creating the impression of a constant pitch.45,48 An acceptable tone color may vary depending on the repertoire, and so too may the vibrato rate. Exceptionally fast and exceptionally slow vibrato rates appear to be important when particularly intense emotions or extreme psychological states are portrayed.48,49 For example, Maria Callas has recorded vibrato rates as fast as 7.1 cycles/second in the mad scene from Donizetti’s opera ‘‘Lucia di Lammermoor,’’51 where the
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Journal of Voice, Vol. 29, No. 2, 2015
character has just murdered her bridegroom, and vibrato rates as slow as 4.1 cycles/second in the sleep-walking scene from Verdi’s opera ‘‘Macbeth,’’52 where the singer is portraying overwhelming emotional disintegration.53 Under more usual circumstances, a rate of 7.1 cycles/second is considered excessively fast,48 and 4.1 cycles/second is unacceptably slow.52 Titze suggests that Pavarotti’s average vibrato rate of 5.5 cycles/second represents a vibrato speed that audiences today find particularly appealing, as it is neither too fast nor too slow. This is in accord with M€ urbe et al47 who classified vibrato below 5.2 cycles/second as slow, and vibrato above 5.8 cycles/ second as fast, and who also found that after 3 years’ tertiary level vocal training, singers were more likely to produce moderate vibrato rates within the range of 5.2–5.8 cycles/second. It is also in accord with the finding that after vocal warm-up there is a tendency for vibrato to draw closer to the region of 5.5 cycles/second.54,55 Thus, with vibrato linked to warming up, to tone color, and to stress and relaxation, and with breathing imagery claiming similar links, the following research questions were posed for the present study. 1. What is the acoustic effect of breathing imagery on singers’ vibrato? 2. Do any changes observed resemble those generally associated with a vocal warm-up?
METHOD Singer background Six classically trained female singers, each from a different studio, participated. Three were studying tertiary level singing, and three had completed tertiary studies and sang professionally (mean age ¼ 29 years, SD ¼ 7 years; mean years of vocal study ¼ 13, SD ¼ 5 years). Singer profiles are presented in Table 1. The use of only female singers prevented genderrelated variables entering into the vibrato analysis. The vocal solo All singers were asked to learn 8 bars from Villa-Lobos’ ‘‘Bachianas Brasileiras No 5 Aria.’’ The vocal range spanned a major
10th from D4 (294 Hz) to F#5 (740 Hz). The excerpt called for a calm, lyrical delivery and considerable vocal beauty for effective performance. The composer required this section to be sung solely on an ‘‘ah.’’ The singers were given the print music, a recording of the accompaniment to be used, and requested not to warm-up on the recording day. It was considered that if the singer had already vocally warmed up such that they were singing their best before the recording session, then perhaps only if an intervention had a detrimental effect on the voice could a change in vocal performance be noted. Recording procedure All singers had individual appointments to record their voices. They were fitted with an AKG C-477 miniature condenser omnidirectional microphone (AKG Acoustics, Vienna, Austria) which was head-mounted so as to maintain a constant distance of 7 cm from the corner of the mouth to the microphone. The microphone was connected to a DAT Marantz compact disc recorder model CDR-640 (Marantz Japan Inc., Kanagawa, Japan) via a Behringer Ultragain Pro MIC-2200 preamplifier (Behringer International, Willich, Germany). Singers were also fitted with Beyerdynamic DT331 free-field earphones (Beyerdynamic GmbH & Co. KG, Heilbronn, Germany) through which to hear the pre-recorded accompaniment. This enabled the voice to be recorded without the accompaniment. It also ensured that all singers maintained an identical tempo, which was necessary as vibrato rate may be influenced by note duration.50 The recording level of the voice was first checked while the singer sang once through the excerpt. As fluctuations in the level of performance stress may influence vibrato characteristics, this process also served to allay singer unfamiliarity with performance conditions. The singers then recorded the excerpt before and after three non-vocal 25 minute tasks. Each singer performed the tasks in a different, randomized order. One task involved imagery of the breath directed up and down as far from the larynx as possible. Another task used Braille music code, which enabled the singer to engage in tactile, kinesthetic and visual imagery related to music but unrelated to breath function. A third task was a non-imagery activity in which the singer completed a cloze passage about breath function. So that all tasks might be perceived as equally valid, the singers
TABLE 1. Singer Profiles SingerSubject
Age (y)
Years of Vocal Study
Vocal Education
Performance Background
1 2 3
19 24 25
7 9 9
Bachelor of Music 1st year Bachelor of Music 2nd year Bachelor of Music 3rd year
4
27
12
Bachelor of Music (Honors)
5 6
49 29
26 16
Diploma of Operatic Art Bachelor of Music; Diploma of Opera
Student examinations Student recitals Student recitals, semi-professional engagements at municipal level Winner of state-wide vocal competitions, state opera Young Artists training program State opera company chorus member, solo recitalist Winner of nation-wide vocal competition, state opera company soloist
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were told that the project was investigating the effect of varying levels of relaxation on the voice. At the completion of recording, singer Sound Pressure Level (SPL) was calibrated using two different dB readings of a 1000 Hz pure sine wave tone and a Rion Integrating Sound Level Meter model NL-06 (Rion Co. Ltd, Tokyo, Japan). For a full account of each intervention see Moorcroft.54 Acoustic analysis All vocal samples were converted into graphic form using the computer software programs Phog Interactive Phonetography System Version 2.0 (Hitech, Sweden) and Soundswell Core Analysis Version 4.0 (Hitech, Sweden). Spectrograms of the 11 sustained notes from each vocal solo (ie, 132 notes per intervention activity, 396 notes in total) were produced and each vibrato cycle assessed for rate and extent. The 11 notes assessed per solo are indicated in Figure 2. The screen resolution for each spectrogram was the result of settings providing the fast Fourier transform (FFT) size 1066/ 2048, frequency range to 5476 Hz, window length 33 ms and a Hanning Window with a bandwidth of 30 Hz. Each spectrogram displayed the undulations of the partials over the length of a selected note. These undulations which represented vibrato cycles were measured by selecting one of the clearly displayed high partials, manually placing a computer cursor over the peak and trough of each vibrato cycle in that partial and registering the corresponding time and frequency from the spectrogram onto a spreadsheet (Excel, Microsoft Office 2000, Redmond, WA). High partials were used, as resolution increases with the partial number.56 From the spreadsheet the registered frequencies were divided by the number of the partial to establish their related fundamental frequencies. To ascertain vibrato extent, the maximum departure from the average fundamental frequency was measured by taking each vibrato cycle, calculating the distance from peak to trough in semitones and dividing the result by two. Hertz were converted into semitones using the formula: 12 log10 ðF0 Þ log10 16:35 F0 in ST ¼ log10 2 Vibrato rate was measured from the time difference between adjacent vibrato peaks and expressed in cycles per second. For both vibrato rate and vibrato extent, the mean values and corresponding standard deviations were calculated for the following:
For the group of singers as a whole under each condition, For each solo under each condition, and For each of the 11 sustained notes in each solo. In addition, from the 11 mean vibrato rates per solo, the fastest, slowest and median values were selected to observe the range of vibrato rates for each solo and the average range of vibrato rates per condition. Changes in both vibrato rate and vibrato extent were also compared with SPL changes. SPL was measured in decibels and established from the graphic representation of an upper and a lower calibration tone recorded directly after each singer’s solos. Mean SPL was extracted from each solo using the Hitech Soundswell Core Analysis histogram function with a resolution setting of 512 bins. Acoustic data were subject to statistical analysis using SPSS (Statistical Package for the Social Sciences v 16; SPSS Inc, Chicago, IL). The design of the study was a fully randomized cross-over block design, in which each singer received each intervention in random order. Repeated measures multivariate analyses of variance were used to analyze the results. The study comprised a 6 3 2 design: (six dependent measures: mean vibrato rate, standard deviation, fastest vibrato rate, slowest vibrato rate, median vibrato rate, and the range of vibrato rates [ie, fastest minus slowest vibrato rate]) by time (before intervention and after intervention). Data were subjected to analysis using the general linear model (GLM). Main effects for time and condition and interaction effects (time 3 condition) were calculated for each dependent measure. A further set of analyzes were conducted to assess the effect of order of intervention on the outcome of the six dependent measures. The analysis was a single factor within subject repeated measures design, with the difference score for each dependent variable calculated by subtracting pretest from the posttest scores. All first, second, and third presentation difference scores were compared to assess possible order effects. The distributions for each dependent measure were assessed for normality and outliers. Examination of skewness and kurtosis statistics indicated that the distributions were relatively normally distributed. Mauchly’s test of sphericity was assessed before interpreting the F statistics from the GLM. Those variables with significance >0.05 were interpreted using the sphericity assumed statistics; those with significance 0.05 were interpreted using the Huynh-Feldt epsilon adjustment.
FIGURE 2. The 11 notes acoustically assessed for vibrato rate and vibrato extent.
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FIGURE 3. The mean and median vibrato rates for the solo, and the mean fastest and mean slowest vibrato rates from each singer’s 11 long held notes per solo. RESULTS Pre- to posttest vibrato rate changes for the group as a whole are presented in Figure 3. As indicated in Figure 3, after the breathing imagery, although no significant change occurred in the group mean (mean change ¼ 0.13, P ¼ 0.15) or median (mean change ¼ 0.06, P ¼ 0.47) vibrato rates, there was a significant reduction in the range of mean vibrato rates for the group (mean change ¼ 0.52, P ¼ 0.02). In contrast, after the Braille music imagery, there was a significant reduction in the group mean (mean change ¼ 0.17, P ¼ 0.01) and median (mean change ¼ 0.18, P ¼ 0.01) vibrato rates, and no significant reduction in the range of mean vibrato rates for the group (mean change ¼ 0.19, P ¼ 0.10). After the cloze passage on breathing, no significant changes were found in either the group mean (mean change ¼ 0.0, P ¼ 0.87) or median (mean change ¼ 0.03, P ¼ 0.38) vibrato rates, nor in the range of mean vibrato rates for the group (mean change ¼ 0.05, P ¼ 0.64). Each singer’s pre- and post-intervention mean vibrato rate is presented in Figure 4.
Breathing imagery 6.4 1
6.3
6.4 1
6.3
6.2
6.2
6.2
6.1
6.1
6.1
6.0
6.0
5.9
5.9
5.8 5.7 5.6
5 6
5.5 5.4 5.3
4
5.8 5.7
5.9
5
5.6 5.5 5.4 5.3
4 6
5.8
5.6
5.4
5.1
5.1
5.1
5.0
5.0
4.9
4.8
After
4
5.0
3
4.9
Before
6
5.3 5.2
4.8
5
5.5
5.2
3
2
5.7
5.2
4.9
1
6.0 2 Cycles per second
2
Cycles per second
Cycles per second
Cloze passage
Braille imagery
6.4 6.3
As indicated, the pre-intervention vibrato for the professional singers 4, 5, and 6 was consistently more moderate (ranging from 5.35–5.73 cycles/second) than that of the student singers who produced both faster (singers 1 and 2) and slower (singer 3) vibrato. However, after the breathing imagery, mean vibrato rates faster than 5.6 cycles/second became slower, and mean vibrato rates below 5.4 became faster. Even the professional singers’ mean vibrato rates compacted to between 5.42 and 5.58 cycles/second. By contrast, after the Braille music imagery, all singers produced slower mean vibrato rates for the solo. Singers with the fastest mean vibrato rates slowed the most. The non-imagery cloze passage produced the least change in mean vibrato rates for the solo. The results of the repeated measures Analysis of Variation (ANOVA), as reported in Table 2, show a significant pre- to post-test difference in vibrato rates for the breathing imagery and the Braille imagery, but not for the cloze passage. A significant pre- to post-test difference between the 11 notes assessed occurred only for the breathing imagery. Figure 5 illustrates the variation in vibrato rates when
3
4.8
Before
After
Before
FIGURE 4. Mean vibrato rates for each of the six singers, pre- and post-intervention.
After
Lynda Moorcroft, et al
TABLE 2. Results of the Repeated Measures ANOVA for Mean Vibrato Rates in Each Solo
Condition
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Vibrato Following Imagery
P Value for Change Over Time (Pre vs Post)
P Value for Differences Between 11 Notes
0.001
