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UID:20250802T053156EDT-7405P3REft@132.216.98.100
DTSTAMP:20250802T093156Z
DESCRIPTION:Title: Markov-Switching State Space Models For Uncovering Music
 al Interpretation.\n\n\n	Abstract:\n\n\nFor concertgoers\, musical interpre
 tation is the most important factor in determining whether or not we enjoy
  a classical performance. Every performance includes mistakes—intonation i
 ssues\, a lost note\, an unpleasant sound—but these are all easily forgott
 en (or unnoticed) when a performer engages her audience\, imbuing a piece 
 with novel emotional content beyond the vague instructions inscribed on th
 e printed page. In this research\, we use data from the CHARM Mazurka Proj
 ect—forty-six professional recordings of Chopin’s Mazurka Op. 68 No. 3 by 
 consummate artists—with the goal of elucidating musically interpretable pe
 rformance decisions. We focus specifically on each performer’s use of musi
 cal tempo by examining the inter-onset intervals of the note attacks in th
 e recording. To explain these tempo decisions\, we develop a switching sta
 te space model and estimate it by maximum likelihood combined with prior i
 nformation gained from music theory and performance practice. We use the e
 stimated parameters to quantitatively describe individual performance deci
 sions and compare recordings. These comparisons suggest methods for inform
 ing music instruction\, discovering listening preferences\, and analyzing 
 performances.\n\nZOOM MEETING\n\nhttps://mcgill.zoom.us/j/83436686293?pwd=
 b0RmWmlXRXE3OWR6NlNIcWF5d0dJQT09\n\nMeeting ID: 834 3668 6293\n\nPasscode:
  12345\n
DTSTART:20220909T193000Z
DTEND:20220909T203000Z
SUMMARY:Daniel McDonald (University of British Columbia)
URL:/mathstat/channels/event/daniel-mcdonald-universit
 y-british-columbia-341395
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