CITATION — REFERENCE ENTRY

rehearsal-learning · raphael2010-music-plus-one

Revision c2f37f20-395c-4273-a3f2-edfd71814964 · 11/1/2026, 4:50:43 PM UTC
Claim ID
rehearsal-learning
Assertion
Music Plus One must perform reasonably well without rehearsal and improve with rehearsal: after rehearsals it re-estimates its timing model to the soloist using the EM algorithm, training on the most recent several rehearsals because the soloist's interpretation drifts. It learns musicality by imitation, which suits the concerto setting but not settings needing independent musicality, such as accompanying early-stage students or opera, where its performance was poorest.
Quote
Our system must improve with rehearsal. [...] the system must "sightread" (perform without rehearsal) reasonably well. [...] Using one or more such rehearsals we can iteratively reestimate the model parameters {µn} using the EM algorithm, resulting in both measurable and perceivable improvment of prediction accuracy. [...] For this reason we train the model using the most recent several rehearsals, thus facilitating the continually evolving nature of musical interpretation. [...] Our system learns its musicality through "osmosis." [...] This manner of learning by imitation works well in the concerto setting [...]. Such a situation occurs with the early-stage accompaniment problem discussed in Section 1, as here one cannot learn the desired musicality from the live player. Perhaps the accompaniment antithesis of the concerto setting is the opera orchestra [...]. We observed the nadir of our system's performance in an opera rehearsal where our system served as rehearsal pianist.
Quote language
en
Locator
section: 4–5
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