Automatic music transcription and audio source separation

M. D. Plumbley, S. A. Abdallah, J. P. Bello, M. E. Davies, G. Monti, M. B. Sandler

Research output: Contribution to journalArticle

Abstract

In this article, we give an overview of a range of approaches to the analysis and separation of musical audio. In particular, we consider the problems of automatic music transcription and audio source separation, which are of particular interest to our group. Monophonic music transcription, where a single note is present at one time, can be tackled using an autocorrelation-based method. For polyphonic music transcription, with several notes at any time, other approaches can be used, such as blackboard model or a multiple-cause/sparse coding method. The latter is based on ideas and methods related to independent component analysis (ICA), a method for sound source separation.

Original languageEnglish (US)
Pages (from-to)603-627
Number of pages25
JournalCybernetics and Systems
Volume33
Issue number6
DOIs
StatePublished - Sep 2002

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Artificial Intelligence

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    Plumbley, M. D., Abdallah, S. A., Bello, J. P., Davies, M. E., Monti, G., & Sandler, M. B. (2002). Automatic music transcription and audio source separation. Cybernetics and Systems, 33(6), 603-627. https://doi.org/10.1080/01969720290040777