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Author Raphael, Christopher
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Abstract A system for musical accompaniment is presented in which a computer-driven orchestra follows and learns from a soloist in a concerto-like setting. The system is decomposed into three modules: The first computes a real-time score match using a hidden Markov model; the second generates the output audio by phase-vocoding a preexisting audio recording; the third provides a link between these two, by predicting future timing evolution using a Kalman Filter--like model. Several examples are presented showing the system in action in diverse musical settings. Connections with machine learning are highlighted, showing current weaknesses and new possible directions.
Description Affiliation: Indiana University, Bloomington, IN (Raphael, Christopher)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2005-08-01
Publisher Place New York
Journal Communications of the ACM (CACM)
Volume Number 54
Issue Number 3
Page Count 7
Starting Page 87
Ending Page 93

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Source: ACM Digital Library