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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 (s): Benetos, Emmanouil;
Affiliation:
Queen Mary University of London, London, UK
(See document for exact affiliation information.)
Publication Date:
2017-06-06
Session subject:
Automatic Music Transcription
DOI:
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Benetos, Emmanouil; 2017; Polyphonic Note and Instrument Tracking Using Linear Dynamical Systems [PDF]; Queen Mary University of London, London, UK; Paper 4-2; Available from: https://aes.org/publications/elibrary-page/?id=18760
Benetos, Emmanouil; Polyphonic Note and Instrument Tracking Using Linear Dynamical Systems [PDF]; Queen Mary University of London, London, UK; Paper 4-2; 2017 Available: https://aes.org/publications/elibrary-page/?id=18760
@inproceedings{Benetos2017polyphonic,
title={{Polyphonic Note and Instrument Tracking Using Linear Dynamical Systems}},
author={Benetos, Emmanouil},
year={2017},
month={jun},
booktitle={Journal of the Audio Engineering Society},
publisher={Paper 4-2; AES Conference: 2017 AES International Conference on Semantic Audio; June 2017},
number={4-2},
organization={AES},
}
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