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%.
| Author: | C. Gregor van den BoogaartGND, Rainer LienhartGND |
|---|---|
| URN: | urn:nbn:de:bvb:384-opus4-11118 |
| Frontdoor URL | https://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 Maschinelles Lernen und Maschinelles Sehen | |
| Dewey Decimal Classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
| Licence (German): |  Deutsches Urheberrecht |
