Post on 13-Apr-2018
Performing BrahmsSimilarities in cello playing styles on record
30 May 2007 Centre for Digital Music Seminar, Queen Mary, University of London
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Structure of talk• Computational (or systematic) musicology
– sound analysis
• Performing Brahms– a preliminary musicology user report of the C4DM
existing tools for analysing musical processing in sound
• What can be helpful?– from the OMRAS2 existing tools of both Goldsmiths &
Queen Mary (for the time being) with further...
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Useful links• OMRAS2: Online Music
Recognition And Searching, C4DM, Queen Mary & Goldsmiths Digital Studios
• CHARM: The AHRC Research Centre for the History and Analysis of Recorded Music
• CPS: Centre for Performance Science, Royal College of Music
• IMR: Institute of Musical Research, University of London
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Working title• Cello Performing Tradition on Record:
A Sound Analysis
• keywords artists similarity
cultural history
legendary cellists
machine learning
music perception
J.S.Bach BWV1007 iv & v; Chopin Op.3; Brahms Op.99 ii; Prokofiev Op.115 ii
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Some key readings
Eric Clarke and Nicholas Cook, 2004 [eds.] Empirical Musicology: Aims, Methods, Prospects. (Oxford: OUP)
John Rink, 1995 [ed.] The Practice of Performance: Studies in Musical Interpretation (Cambridge: CUP)
Bruno Repp, 1992-2002 articles in Journal of Acoustical Society of America
ICMPC and ISMIR proceedings
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Previous works on sound analysis• Music psychologists
– Intonation, vibrato (Seashore et al 1934)– Timing and dynamic (Clarke 1984, 1995; Windsor and
Clarke 1997; Repp 1992, 1998, 1999)
• Music IR engineers– Timing (Dixon 2001, 2003 etc)– Ornaments (Casey and Crawford 2004)
• Musicologists– Timing (Bowen 1996, 1999; Cook 1987, 1995, 2002)– Portamento (Leech-Wilkinson 2006)
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Sound analysis: similarities & ...
Music Psychology Music IR Musicology
Materials produce own recordings from lab existing audio recordings existing audio recordings
Measurement significant interests as a demonstration of "tool" some interests
Interpretation some interests not so much interested significant interests
Perception human "listening" participants machine listening interaction between his "own"
and machine listening
Statistics Qualitative and Quantitative data with ref to "tool" development data related
Tool development not interested most significant interests depends on…
Collaborations performing musicians industry computer programmers?
non-musicians musicologists
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The role of systematic musicologists
• Measuring behavioural aspects of artists from musical processing (rhythm, loudness, pitch) in sound
• Interpreting the captured data in musical language and context
• Quantitative audio data handling -- statistical analysis
• bridging a gap between musicology and music IR
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Computational tools used:• Sonic Visualiser
– Timing fluctuation in a global frame: reverse conducting – Measurement of performance hierarchy intensity level (data
can also be obtained through the Praat).
• BeatRoot– Rhythmic irregularity in a (repeat) performance structure:
IOI (performed score duration)
• MATCH– Alignment of all the investigated recordings
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Investigated recordings: Brahms, Op.99, ii
Dates Artists Label Mvt duration Tempo
1936 Casals (cello) Horszowski (piano) HMV DB3059/62 08:01 Q = 401966 Piatigorsky (cello) Rubinstein (piano) RCA Victor 09026 62592 2 07:44 Q = 441968 Du Pré (cello) Barenboim (piano) EMI 7 63298 2 07:31 Q = 421985 Yo-Yo Ma (cello) Ax (piano) RCD!-7022 07:45 Q = 44
1986 Rostropovich (cello) Richter (piano) 410 510-2 GH 08:27 Q = 38
1999 Maisky (cello) Gililov (piano) 458 677-2 GH 06:50 Q = 50
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Relationship tree of cellists
E Feuermann1902-1942
P Casals1876-1973
J Du Pre1945-1987
M Rostropovich1927-2007
G Cassado1897-1966
M Maisky1948-
M Gendron1920-1990
W Pleeth1916-1999
A direct lineage of teacher-student relation
G Piatigorsky1903-1076
J Klengel1859-1933H Becker
1864-1941
B Harrison1892-1965
Y-Y Ma1955-
L Rose1918-1984
A Ivashkin1948-
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Casals on dynamic shaping
• Casals’ principle on dynamic phrasing– Melodic contour and
dynamic shaping: pitch higher - dynamic louder
– always exceptional cases
• Sibelius algorithm Espressivo– pitch higher - dynamic
louder
Sibelius algorithm
CasalsdB
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Casals’s rubato
• For Casals, the “authentic” tempo is impossible (Corredo 1956: 123).
• The tempo should vary with the performer according to the circumstances.
• “swing-like”: flexible and precise
Bar 13 & 21, Menuet I, J.S.Bach BWV1007,
Casals’s performed score duration: IOI data captured through BeatRoot.
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Reverse conducting: Sonic Visualiser
• Sonic Visualiser see http://www.charm.rhul.ac.uk/content/svtraining/intro.html
• Timing see http://www.soton.ac.uk/~musicbox/charm5.html
Brahms, Op.99, ii, Y-Y Ma
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Beat level analysis: repeat structure
Casals (1936), J.S.Bach BWV1007 Sarabande: data captured through Sonic Visualiser
0
0.5
1
1.5
2
2.5
bars
IOI:
seco
nd
s
1b_1 2b_1 3b_1 1b_r 2b_r 3b_r
1 95 13
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Beat tracking -- BeatRoot
• Inter-onset-interval IOI: performed score duration
• The user can manually correct machine errors
• provides measurement readings
Brahms, Op.99, ii, b1-19, Du Pré
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Rhythmic irregularities
Casals (1936), J.S.Bach BWV1007 Sarabande: data captured through BeatRoot
0
50
100
150
200
250
300
350
1st repeat
2/1 /2 6/2 /3 7/1 13/3 14/1
IOI:
ms
bars/beat
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Grouping structure: Brahms’s Op.99, ii
Phrase Grouping Key Boundary CadenceA: b1-11 4+4+3 F# major I-V HC
b12-19 4+4 F# major I-V HCB: b20-28 3+5 F minor vii-I AC
b29-43 4+4+3+4 Gb major ii-V HCA: b44-55 4+4+4 F# major ii-V HC
b56-71 4+3+3+6 F# major V-I AC
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Audio alignment: MATCH
• Audio alignment of exposition (bars 1-19) & recapitulation (bars 44-71) on the six investigated recordings– NB. bars 44-52 in recap
is identical to bars 1-9
• demo
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Intensity analysis Praat vs. Sonic Visualiser
Brahms, Op.99, ii, b1-19, Casals Brahms, Op.99, ii, Casals
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Intensity analysis Praat vs. Sonic Visualiser
Praat Sonic Visualiser
Visualisation not efficient setting changeable
Measurement v v
"Relative" level setting changeable currently unavailable
Analysable duration length 3 min 30 sec no limitation
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Dynamic peaks: Brahms, Op.99, ii, bars 1-19
Cellists Performance hierarchy dynamic measurementCasals F#4: b5 b5-10 C#5: b8 E#5: b15
58.6 dB crescendo 66.9 dB 62.6 dBPiatigorsky F#4: b5 b5-10 C#5: b8 D#5: b10 E#5: b15
51.9 dB crescendo 67.9 dB 66.2 dB 65.4 dBDu Pré F#4: b5 b5-10 C#5: b8 C#5: b10 E#5: b15
50.7 dB crescendo 71.8 dB 69.7 dB 67.6 dBY-Y Ma F#4: b5 b5-10 C#5: b8 D#5: b10 A#5: b15
54.9 dB crescendo 64.24 dB 66.24 dB 65.67 dBRostropovich F#4: b5 b5-10 C#5: b8
58 dB crescendo 72.6 dBMaisky F#4: b5 b5-10 C#5: b8
63.1 dB crescendo 74 dB
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Tempo Modification: Brahms, Op.99, ii
0
1
2
3
4
5
6
7
CasalsPiatigorskyDu PreY-Y MaRostropovichMaisky
[Exposition] [Development] [Recapitulation]
seco
nd
s
12
20
28
44
48
56 71
bars
performed score duration: data captured through Sonic Visualiser
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Correlation on timing
x = Casals’ timing, y = Y-Y Ma’s, observations: 142
r = 0.37, t = 4.79, (p = 0.000004)
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Correlation on timing
Teacher-student timing fluctuations correlation t-test p valueCasals's timing vs. Du Pré's r = 0.6 t = 8.91 p < 0.0000001
Casals's vs. Y-Y Ma's r = 0.37 t = 4.79 p = 0.000004Random relation timing fluctuations correlation t-test p value
Casals's vs. Piatigorsky's r = 0.5 t = 7.51 p < 0.0000001Casals's vs. Rostropovich’s r = 0.4 t = 5.23 p = 0.000001
Casals's vs. Maisky's r = 0.51 t = 7.15 p < 0.0000001
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IOI: performed score duration Brahms, Op.99, ii, bars 1-19
500
800
1100
1400
1700
2000
Casals
DuPre
Y-YMa
[4+4+3] [4+4]
IOI
ms
5 9 12
16
19bars
performed score duration: data captured through BeatRoot.
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Correlation on timing
Teacher-student timing fluctuations correlation t-test p valueCasals's timing vs. Du Pré's r = 0.63 t = 10.02 p < 0.0000001
Casals's vs. Y-Y Ma's r = 0.52 t = 7.55 p < 0.0000001Random relation timing fluctuations correlation t-test p value
Casals's vs. Piatigorsky's r = 0.55 t = 7.98 p < 0.0000001Casals's vs. Rostropovich's r = 0.41 t = 5.51 p < 0.0000001
Casals's vs. Maisky's r = 0.14 t = 1.79 p = 0.07
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What can be helpful?Goldsmiths Digital Studios
Soundspotter versions 1 (& 2)
sub-space analysis
Repeat structure detecting tool
as shown in the Mazurka case study
C4DM, Queen MaryBeatRoot
intensity level measurement option from the zwicker model
Sonic Visualiser
3 items submitted in the features tracker
Soundbite
Windows version, please!