POLYPHONIC PIANO TRANSCRIPTION USING NON-NEGATIVE MATRIX FACTORISATION WITH GROUP SPARSITY

被引：0
|
作者：
O'Hanlon, Ken [1 ]
Plumbley, Mark D. [1 ]
机构：
[1] Queen Mary Univ London, London, England
来源：
2014 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2014年
关键词：
Automatic music transcription; non-negative matrix factorisation; group sparsity; MUSIC; ALGORITHMS;
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
Non-negative Matrix Factorisation (NMF) is a popular tool in musical signal processing. However, problems using this methodology in the context of Automatic Music Transcription (AMT) have been noted resulting in the proposal of supervised and constrained variants of NMF for this purpose. Group sparsity has previously been seen to be effective for AMT when used with stepwise methods. In this paper group sparsity is introduced to supervised NMF decompositions and a dictionary tuning approach to AMT is proposed based upon group sparse NMF using the beta-divergence. Experimental results are given showing improved AMT results over the state-of-the-art NMF-based AMT system
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页数：5
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