In this paper, a system for automatic transcription of multiple-instrument polyphonic music is proposed, which supports tracking multiple concurrent notes using linear dynamical systems (LDS). The system is based on a spectrogram factorisation model and supports the detection of multiple pitches and instrument contributions. In order to track multiple concurrent pitches, the use of LDS as prior to the multi-pitch model is proposed. LDS parameters are learned using score-informed transcriptions; for inference, online and offline LDS variants are evaluated. The MAPS and Bach10 datasets are used for experiments. Results show that the proposed LDS-based method can successfully track multiple concurrent notes, leading to an improvement of over 3% in terms of F-measure for both datasets over benchmark note tracking approaches.

Author: Benetos, Emmanouil
Affiliation: Queen Mary University of London, London, UK
AES Conference: 2017 AES International Conference on Semantic Audio (June 2017)
Paper Number: 4-2
Publication Date: June 13, 2017
Subject: Automatic Music Transcription

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