単音連繋確率ネットワークに基づく音楽演奏の音源同定

概要

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Sound source identification is an important but difficult problem in sound source separation. It is also a problem in the symbolization of music performances which include multiple simultaneous notes. As a solution to this problem, this paper presents a new method that can significantly improve the precision of sound source identification for music. Identification is here defined as the recognition of instrument names for each note included in an ensemble music monaural (or stereo) signal. The key idea of the proposed method is utilizing musical context. First we define the "music stream" that corresponds to a sequence of notes as a basic representation of musical context. We then describe the Bayesian method to introduce the contextual information to sound source identification. Experimental results show that the proposed method improves the accuracy of the source identification task for three-part ensemble music signals from an average of 67.8 % to 88.5 %.
社団法人人工知能学会の論文
1998-11-01