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"Assessing the capacities of the self-defined tone-deaf : Deconstructing a myth"

"Assessing the capacities of the self-defined tone-deaf : Deconstructing a myth". John Sloboda and Karen Wise (Centre for Psychology Research: Research Institute of Life Course Studies) j.a.sloboda@psy.keele.ac.uk k.j.wise@psy.keele.ac.uk. Acknowledgments. Funding from the British Academy

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"Assessing the capacities of the self-defined tone-deaf : Deconstructing a myth"

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  1. "Assessing the capacities of the self-defined tone-deaf:Deconstructing a myth" John Sloboda and Karen Wise (Centre for Psychology Research: Research Institute of Life Course Studies) j.a.sloboda@psy.keele.ac.uk k.j.wise@psy.keele.ac.uk

  2. Acknowledgments Funding from • the British Academy • The Leverhulme Trust • The Nuffield Foundation • Society for Education, Music and Psychology Research

  3. Context • Long-term Keele-based work on understanding individual differences in musical skill • Motivation: - Scientific explanation of musical variation - Seeking underlying commonalities - Rescuing extremes from the status of “freaks”

  4. Work at Keele • Phenomena studied - Musical savants (low IQ individuals with high musical skills) With Neil O’Connor and Beate Hermelin (1980s) - Exceptionally skilled young musicians (the musically “gifted”) With Michael Howe, Jane Davidson, and Derek Moore (1990s) - People who have, or believe themselves to have, musical deficits (the “tone deaf” or “amusics”) With Isabelle Peretz and Karen Wise, and support from Lauren Stewart (Goldsmiths University) - ongoing

  5. Influences on skill acquisition • Determinants of high ability include cognitive, social, and motivational variables Key examples • COGNITIVE Practice – strong relationship between amount of relevant cognitive effort and achievement • SOCIAL Adult support behaviour – strong relationship between nature and amount of parental support and achievement

  6. PRACTICE

  7. Motivational variables • MOTIVATIONAL Mastery-orientation, belief in self as “talented” – strong relationship between self-beliefs and persistence on difficult tasks BUT • Lay beliefs about causes of high achievement include the postulation of rare “innate talent”, the lack of which is held to explain low achievement. • Large numbers in western society consider themselves “unmusical”, have objectively low achievement, and have “given up” on aspirations to musical skill acquisition

  8. Developmental considerations • Yet perceptual and cognitive studies of babies suggest sophisticated inborn mechanisms for processing musical sounds, with few individual differences. • Therefore, a parsimonious assumption is that lack of achievement is not generally due to a lack of cognitive capacity. • Are there people who really do lack essential cognitive capacities? The “tone deaf”? • If so, is it possible to screen for “tone deafness”, thereby proving to the “not tone deaf” that they have the requisite capacity, and could this proof re-motivate them to engage in musical skill acquisition activities?

  9. Current research programme • Develop a comprehensive assessment battery capable of differentiating among different types of musical “under-performance” • Through this battery begin to more precisely map out (and offer functional accounts of) different patterns of deficit in the general population • Most specifically, use the battery to investigate differences between identified “congenital amusics” (Peretz et al), self-defined “tone-deaf” adults, and adult controls.

  10. “Congenital amusia” (Ayotte, Peretz & Hyde, 2002) • Peretz et al – Montreal sample • Allegedly emerges in early life and persists in adulthood • Normal perception and cognition otherwise • Dense Impairments in melodic discrimination and recognition, musical memory, metric discrimination, singing, and tapping with the beat • May affect 4% of population (Kalmus & Fry, 1980) • Montreal Battery for the Evaluation of Amusia (MBEA) reliably distinguishes amusics from others. Amusics perform at chance, normals perform well. • This is a purely perceptual test, requires no musical performance

  11. Are tone deafness and amusia the same things? • 17% of university undergraduates self-define as tone deaf, but most score in the normal range on the MBEA (Cuddy, 2005) So: • Either they do not have difficulties but believe they do • Or they have difficulties not detected by the MBEA • Understanding and assisting this large sub-population requires differentiating between these possibilities

  12. Concepts of ‘tone deafness’ No scientific definition. Lay term. Interviews have revealed: • Tone deafness is generally associated with a (perceived) inability to sing • Tone deafness is not just an extreme form of unmusicality: a person can be both musical and tone-deaf • Comparative judgements of singing performance are at the centre of many self-assessments (Sloboda, Wise & Peretz, Annals of NY Academy of Sciences 2005)

  13. Groups and measures: overview Groups: Self-defined ‘Tone Deaf ‘(STD) (N=13) Keele Self-defined ‘Not Tone Deaf ‘(NTD) (N=17) Keele ‘Congenital Amusics’ (CA) (N = 12) Montreal/London Measures: PERCEPTION • MBEA; New MBEA sub-tests • pitch direction judgement: Non-vocal pitch matching (computer) PRODUCTION • Basic vocal control & range (speech & singing) • Singing (matching pitches and short patterns; songs) SELF REPORT • self-assessment of performance; background questionnaire

  14. Possible deficit patterns: and hypothesised functional causes ‘X’ = poor performance relative to published norms or controls ‘A’ = average or above average performance relative to published norms or controls

  15. Groups and measures: overview Groups: Self-defined ‘Tone Deaf ‘(STD) (N=13) Keele Self-defined ‘Not Tone Deaf ‘(NTD) (N=17) Keele ‘Congenital Amusics’ (CA) (N = 12) Montreal/London Measures: PERCEPTION • MBEA; New MBEA sub-tests • pitch direction judgement: Non-vocal pitch matching (computer) PRODUCTION • Basic vocal control & range (speech & singing) • Singing (matching pitches and short patterns; songs) SELF REPORT • self-assessment of performance; background questionnaire

  16. Montreal Battery of Evaluation of Amusia (MBEA) Six existing normed subtests: • Melodic discrimination: Scale Interval Contour • Temporal discrimination: Metre Rhythm • Musical memory: Recognition Same pool of 30 melodies for each test Same-different judgement on 2 sequences

  17. MBEA – scale test example • Sound example

  18. MBEA results Mean scores: STD = 81.04, NTD = 85.58

  19. Adding new sub-tests to the MBEA • (a) emotional perception • (b) harmony perception • Using same melody pool and same task (same-different judgement)

  20. Emotion sub-test • Professional performers can effectively communicate basic emotions (happy-sad) through performance variation (Juslin 1997) • Professional violinist recorded each tune in 4 ways: happy very happy sad very sad

  21. Emotion judgement Are the two performances communicating the same emotion or different emotions? • Sound example • Sound example

  22. MBEA scores –old and new tests

  23. Real ability or artifact? • It may be that Amusics are capable of processing and appropriately categorising at least one aspect of musical sequences where this does not depend on fine pitch discrimination • But they may be making judgement on non-musical bases (e.g. long vs short duration of stimulus) • Current redesign of test to make all stimuli the same duration.

  24. Harmony sub-test Three harmonisations for each melody (a) Conventional (diatonic chords from key of melody leading to perfect or plagal cadence)

  25. Standard harmonisation

  26. Alternate harmonisations (last 2 chords only) • (b) Mildly unconventional (using chords from the key, but avoiding plagal and perfect cadence) • (c) Highly unconventional (using chords from outside the key)

  27. Harmony judgement Are the two sequences the same or different? • “Same” examples repeated the conventional harmonisation twice • “Different” examples paired a conventional with an unconventional harmonisation.

  28. MBEA normals versus amusics

  29. Harmony test • Sub-group performance • All groups significantly different from one another • (STD range = 13 – 18)

  30. Purpose of enhanced MBEA wider range of abilities tested increased potential for differentiating population sub-groups

  31. MBEA overview • Congenital amusics generally perform poorly on a harmonic same-different task (as poorly as other pitch-based tasks) • Congenital amusics generally perform like normals on an emotion same-different task (and at ceiling). • People who self-define as tone-deaf have MBEA scores close to (but still significantly lower than) normals. They do not share the same deficit profile as congenital amusics. • Deeper understanding of the nature of these deficits will require tests of production and self-ratings on specific tasks.

  32. Recent data from Amusics • New data, as yet incomplete • Impossible to give more than a flavour – most quantitative results from here on don’t include CAs • Key observation is that CAs are not a homogeneous group. Some perfomed above chance on some of our new tasks, some did very badly. • Raises possibility of a) several separable deficits and b) different deficits underlying the ‘typical’ amusic behaviour profile • Is congenital amusia really (just) a pitch perception deficit?

  33. Groups and measures: overview Groups: Self-defined ‘Tone Deaf ‘(STD) (N=13) Keele Self-defined ‘Not Tone Deaf ‘(NTD) (N=17) Keele ‘Congenital Amusics’ (CA) (N = 12) Montreal/London Measures: PERCEPTION • MBEA; New MBEA sub-tests • pitch direction judgement: Non-vocal pitch matching (computer) PRODUCTION • Basic vocal control & range (speech & singing) • Singing (matching pitches and short patterns; songs) SELF REPORT • self-assessment of performance; background questionnaire

  34. Pitch direction judgement • Participants judge ‘up’ ‘down’ or ‘same’ for pairs of piano tones • Ceiling effect • Some amusics do well • Different patterns of low scores • Difficulty spotting changes • Difficulty identifying direction of changes

  35. Non-vocal pitch-matching • Computer task involving adjusting one movable tone to match a fixed tone • Boxplot shows mean deviation in cents from the target • Difference between TD and NTD groups only significant with outliers removed • Amusics much worse than any other group – most accurate performance was on average nearly a semitone off-target.

  36. Groups and measures: overview Groups: Self-defined ‘Tone Deaf ‘(STD) (N=13) Keele Self-defined ‘Not Tone Deaf ‘(NTD) (N=17) Keele ‘Congenital Amusics’ (CA) (N = 12) Montreal/London Measures: PERCEPTION • MBEA; New MBEA sub-tests • pitch direction judgement: Non-vocal pitch matching (computer) PRODUCTION • Basic vocal control & range (speech & singing) • Singing (matching pitches and short patterns; songs) SELF REPORT • self-assessment of performance; background questionnaire

  37. Objectives: To test the theory that poor singing is linked to a restricted singing pitch range To establish possible underlying causes of a restricted range, in particular to rule out low-level physiological problems Taking several different measures of vocal pitch range allows these distinctions to be made Basic vocal control & range (1)

  38. Basic vocal control & range (2) • Essential vocal skills for singing: • Pitch change and pitch sustaining • Extent of conscious control • Tasks • Speech contours • Speech-to-singing • Up & down • Sung range • Slides

  39. Basic vocal control & range (3) • Self defined ‘tone deaf’ group have a reduced vocal range overall, but especially in singing • No sig. overall difference between amusics and controls • Polarised singing behaviour in amusic group • Most have wide range • One had a range of less than 3, and the other two did not sustain pitches

  40. Alternative way of showing vocal range data

  41. Groups and measures: overview Groups: Self-defined ‘Tone Deaf ‘(STD) (N=13) Keele Self-defined ‘Not Tone Deaf ‘(NTD) (N=17) Keele ‘Congenital Amusics’ (CA) (N = 12) Montreal/London Measures: PERCEPTION • MBEA; New MBEA sub-tests • pitch direction judgement: Non-vocal pitch matching (computer) PRODUCTION • Basic vocal control & range (speech & singing) • Singing (matching pitches and short patterns; songs) SELF REPORT • self-assessment of performance; background questionnaire

  42. Matching pitches and short patterns • Battery consists of: • 6 x single pitches • 4 x 2-note patterns • 4 x 3-note patterns • 4 x 5-note patterns • All in same key, within comfortable untrained singing range, and composed to make musical sense • Sung by a model of participant’s own gender to neutral syllable ‘na’ • 2 conditions (counterbalanced, within participants) • Echo • Synchronised

  43. Pitch/pattern matching analysis • Fundamental frequency calculated for each note • Accuracy = mean difference between model pitches and participant’s sung pitches, in cents (100 cents = 1 semitone) • Absolute values were used to avoid –ve and +ve differences cancelling each other out

  44. Pitch/pattern matching results Mean cents deviation: Echo Mean cents deviation: Sync Main effect of length:F(3,81)=36.32, p<.001; Group*length interaction:F(3,81)=5.90, p=.001; Group*condition interaction:F(1,27)= 5.77, p=.023; Condition*length interaction:F(3,81)=4.70, p=.004 (Reprinted from Wise & Sloboda (2007) Musicae Scientiae)

  45. Singing: Songs • Own choice song (not CAs) • Happy Birthday: - Twice unaccompanied at participant’s own choice of pitch - Twice accompanied, once at participant’s comfortable pitch, then either a tone higher or lower (except CAs, who only sang unaccompanied) • Performances rated blind by two independent judges, and self-rated by participants during the session.

  46. Expert accuracy rating scale 8. All melody is accurate and in tune, and key is maintained throughout. 7. Key is maintained throughout, and melody accurately represented, but some mistunings (though not enough to alter the pitch-class of the note) 6. Key is maintained throughout and melody mostly accurately represented, but some errors (notes mistuned sufficiently to be ‘wrong’) 5. Melody largely accurate, but singer’s key drifts or wanders. This may be the result of a mistuned interval, from which the singer then continues with more accurate intervals but without returning to the original pitch. 4. Melody fairly accurate, or mostly accurate within individual phrases, but singer changes key abruptly, especially between phrases (e.g. adjusting higher-lying phrases down). 3. Singer accurately represents the contour of the melody but without consistent pitch accuracy or key stability. 2. Words are correct but pitches sound random, and there are errors in contour. 1. Singer sings with little variation in pitch, and may chant in speaking voice rather than singing.

  47. Results: ‘Happy Birthday’ accuracy scores Inter-rater agreement of above 80% (Reprinted from Wise & Sloboda (2007) Musicae Scientiae)

  48. Singing performance and vocal range (1) • Accuracy of Happy Birthday performance correlates with sung range measure to a great extent; to a lesser extent with speech range measure • But speech and sung ranges do not correlate with each other

  49. Singing performance and vocal range (2) • Despite having the underlying vocal capacity to produce a wider pitch range, the STD group don’t do so in singing – but why? • Sustaining pitches is more vocally strenuous than the gliding pitches typical of speech. Higher vocal registers require a different larynx muscle co-ordination to typical speech register. • But Davidson (1994) suggests that restricting one’s singing range is necessary in the process of developing tonal knowledge • So there may be two possibilities: • Less accurate singers have poorer voice function/skills • Less accurate singers have less stable/accurate tonal representations

  50. Differential predictions • Prediction 1: A low-level motor productive deficit should show in a difficulty performing singing-relevant pitch control tasks outside a musical context, i.e. systematic movement of pitch and sustaining of pitch in non-musical vocal tasks.

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