Note onset detection for the transcription of polyphonic piano music

  • Transcription of music is the process of generating a symbolic representation such as a score sheet or a MIDI file from an audio recording of a piece of music. A statistical machine learning approach for detecting note onsets in polyphonic piano music is presented. An area from the spectrogram of the sound is concatenated into one feature vector. A cascade of boosted classifiers is used for dimensionality reduction and classification in an one-versus-all manner. The presented system achieves an accuracy of 87.4% in onset detection outperforming the best comparison system by 25.1%.

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Metadaten
Author:C. Gregor van den BoogaartGND, Rainer LienhartGND
URN:urn:nbn:de:bvb:384-opus4-11118
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/1318
Series (Serial Number):Reports / Technische Berichte der Fakultät für Angewandte Informatik der Universität Augsburg (2009-11)
Type:Report
Language:English
Publishing Institution:Universität Augsburg
Release Date:2009/10/21
Tag:acoustic signal detection; spectral analysis; feature extraction; pattern classification
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Multimedia und Maschinelles Sehen
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Deutsches Urheberrecht