In this paper, a method for automatic transcription of polyphonic music is proposed that exploits key information. The proposed system performs key detection using a matching technique with distributions of pitch class pairs, called Zweiklang profiles. The automatic transcription system is based on probabilistic latent component analysis, supporting templates from multiple instruments, as well as tuning deviations and frequency modulations. Key information is incorporated to the transcription system using Dirichlet priors during the parameter update stage. Experiments are performed on a polyphonic, multiple-instrument dataset of Bach chorales, where it is shown that incorporating key information improves multi-pitch detection and instrument assignment performance.
Benetos, Emmanouil; Jansson, Andreas; Weyde, Tillman
Affiliation: City University London, London, UK
AES Conference: 53rd International Conference: Semantic Audio (January 2014)
Paper Number: 3-2
Publication Date: January 27, 2014
Subject: Automatic Music Transcription
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