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Transcription and Separation of Drum Signals From Polyphonic Music

Abstract : The purpose of this article is to present new advances in music transcription and source separation with a focus on drum signals. A complete drum transcription system is described, which combines information from the original music signal and a drum track enhanced version obtained by source separation. In addition to efficient fusion strategies to take into account these two complementary sources of information, the transcription system integrates a large set of features, optimally selected by feature selection. Concurrently, the problem of drum track extraction from polyphonic music is tackled both by proposing a novel approach based on harmonic/noise decomposition and time/frequency masking and by improving an existing Wiener filtering-based separation method. The separation and transcription techniques presented are thoroughly evaluated on a large public database of music signals. A transcription accuracy between 64.5% and 80.3% is obtained, depending on the drum instrument, for well-balanced mixes, and the efficiency of our drum separation algorithms is illustrated in a comprehensive benchmark.
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https://hal.inria.fr/hal-02652666
Contributor : Gaël Richard <>
Submitted on : Friday, May 29, 2020 - 7:56:32 PM
Last modification on : Wednesday, September 30, 2020 - 8:54:16 AM

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Olivier Gillet, Gael Richard. Transcription and Separation of Drum Signals From Polyphonic Music. IEEE Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2008, ⟨10.1109/TASL.2007.914120⟩. ⟨hal-02652666⟩

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