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Polyphonic music transcription using note onset and offset detection

Benetos, E. & Dixon, S. (2011). Polyphonic music transcription using note onset and offset detection. In: ICASSP. 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 22 - 27 May 2011, Prague, Czech Republic. doi: 10.1109/ICASSP.2011.5946322

Abstract

In this paper, an approach for polyphonic music transcription based on joint multiple-F0 estimation and note onset/offset detection is proposed. For preprocessing, the resonator time-frequency image of the input music signal is extracted and noise suppression is performed. A pitch salience function is extracted for each frame along with tuning and inharmonicity parameters. For onset detection, late fusion is employed by combining a novel spectral flux-based feature which incorporates pitch tuning information and a novel salience function-based descriptor. For each segment defined by two onsets, an overlapping partial treatment procedure is used and a pitch set score function is proposed. A note offset detection procedure is also proposed using HMMs trained on MIDI data. The system was trained on piano chords and tested on classic and jazz recordings from the RWC database. Improved transcription results are reported compared to state-of-the-art approaches.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: DOI: 10.1109/ICASSP.2011.5946322 © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Publisher Keywords: automatic transcription, multiple-F0 estimation, acoustic signal processing, music information retrieval
Subjects: M Music and Books on Music > M Music
Q Science > QA Mathematics > QA76 Computer software
Departments: School of Science & Technology > Computer Science
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