Beyond the tempo(-loudness) graph

Delivered 12 p.m, Thursday, May 8 2014 at Theorizing Music Temporality (Prof. Mariusz Kozak)

Transcript

1. Beyond the tempo(-loudness) graph Alternatives to visual time-series representations of performance data Eamonn Bell <epb2125@columbia.edu> Theorizing Music Temporality (Prof. Mariusz Kozak) 12 p.m, Thursday, May 8 2014
2. Cook on “structuralist” analyses Structuralist analyses/analysts: 1. “[understand] music to be something inside people's heads, so losing its social dimension” 2. “[understand] music to subsist in structure, which structure can be more or less resolved in to notational categories.” 3. “[conceive] of music in terms of a communicative chain passing from the composer via the performer” 4. are less than careful with the “two senses of ‘expression’: [. . .] its ordinary language meaning where it refers to mood, afect and emotion, and on the other the idea of performance expressing structure” Nicholas Cook, Beyond the Score, 31
3. What is a time-series? “A time series is a sequence of observations which are ordered in time (or space). If observations are made on some phenomenon throughout time, it is most sensible to display the data in the order in which they arose.” – STEPs Statistics Glossary (University of Glasgow) http://www.stats.gla.ac.uk/steps/glossary/time_series.html
4. 1º wave – Alexander Truslit (1938) from Shove and Repp (1992)
5. 2º wave – Manfred Clynes (1969, . . .)
6. 2º wave – Repp (1995) ‘Expressive timing. . .’
7. 2º wave – Palmer (1989)
8. 3º wave – Chew and Callender (2013)
9. 3º wave – Chew and Callender (2013)
10. 3º wave – Ohriner (2012) Example 15 (a). Durational contours of the Mazurka in B minor, op. 30, no. 2, with GFL-refective groups in black [Pertains to Frederic Chiu's recording (1999)]
11. 3º wave – Ohriner (2012) Example 13. GFL-refectivity in performances of the three excerpts given in Example 12
12. “First wave” Truslit, Becker, Sievers ('20s) Seashore (1936) “Second wave” (c. 1980–90) Repp, Palmer, Rink, Clarke* Todd, KTH, Music Perception “Third wave” Cook, Ohriner, Sapp, (Chew) Literature review (in review) Citations >1960 in Ohriner (2012)
13. Time-series representations. . . 1. de-emphasize the potentiality for an accretion of meaning throughout the course of a performance 2. soft-pedal the provisional aspect of performance decisions
14. Towards a better visualization Link to iPython notebook. . . Hagen Quartet – Ravel SQ/II, m. 40–51 http://www.eamonnbell.com/ravelstudy/RavelsecondTime.wav Hagen Quartet – Ravel SQ/II, m. 150–162 http://www.eamonnbell.com/ravelstudy/RavelthirdTime.wav
15. 2v1, 3v2 – Hagen Quartet Hagen Quartet Ravel String Quartet/II, “A1” theme (Red is faster; blue is slower) m. 40–51 vs. m. 1–12 m. 150–162 vs. m. 40–51
16. Larger matrix – Arcanto Quartet Arcanto Quartet Ravel String Quartet/II, “A1” theme
17. Matrix of matrices Ravel String Quartet/II, “A1” theme Performance A Performance B Performance C Performance D
18. Time-series representations. . . 1. de-emphasize the potentiality for an accretion of meaning throughout the course of a performance 2. soft-pedal the provisional aspect of performance decisions
19. Questions Beyond the tempo(-loudness) graph Alternatives to visual time-series representations of performance data Eamonn Bell <epb2125@columbia.edu> Theorizing Music Temporality (Prof. Mariusz Kozak) 12 p.m, Thursday, May 8 2014