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Real-time polyphonic music transcription with non-negative matrix factorization and beta-divergence

Abstract : In this paper, we investigate the problem of real-time polyphonic music transcription by employing non-negative matrix factorization techniques and the beta-divergence as a cost function. We consider real-world setups where the music signal arrives incrementally to the system and is transcribed as it unfolds in time. The proposed transcription system is addressed with a modified non-negative matrix factorization scheme, called non-negative decomposition, where the incoming signal is projected onto a fixed basis of templates learned off-line prior to the decomposition. We discuss the use of non-negative matrix factorization with the beta-divergence to achieve the real-time decomposition. The proposed system is evaluated on the specific task of piano music transcription and the results show that it can outperform several state-of-the-art off-line approaches.
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Contributor : Arnaud Dessein Connect in order to contact the contributor
Submitted on : Friday, June 15, 2012 - 2:59:34 PM
Last modification on : Tuesday, March 15, 2022 - 3:19:46 AM
Long-term archiving on: : Sunday, September 16, 2012 - 2:55:29 AM


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  • HAL Id : hal-00708682, version 1


Arnaud Dessein, Arshia Cont, Guillaume Lemaitre. Real-time polyphonic music transcription with non-negative matrix factorization and beta-divergence. ISMIR - 11th International Society for Music Information Retrieval Conference, Aug 2010, Utrecht, Netherlands. pp.489-494. ⟨hal-00708682⟩



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