Multiphonic Note Identification

Simon Dixon
Department of Computer Science, The Flinders University of South Australia, GPO Box 2100, Adelaide SA 5001, Australia.


This paper describes work in progress which addresses several aspects of perception of sound by a computer. This work forms part of a project to build an automatic music transcription system. In recent years there has been considerable advances in the area of note identification (frequency tracking), to the extent that there are commercial systems which perform well on the task of monophonic note identification. The problem of identifying multiple simultaneous notes remains mostly unsolved, due to the difficulty of separating the partials into their component notes. We present an approach to multiphonic note identification, drawing on research in speech recognition and psychoacoustics. The acoustic data is processed according to a model of human auditory perception and dynamic models of the sources.
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