Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
564528 | Signal Processing | 2009 | 14 Pages |
Abstract
Music transcription consists in transforming the musical content of audio data into a symbolic representation. The objective of this study is to investigate a transcription system for polyphonic piano, triggered by events corresponding to the played notes. The proposed method focuses on note events and their main characteristics: the attack instant, the pitch and the final instant. Onset detection exploits a binary time-frequency representation of the audio signal. Note classification and offset detection are based on constant Q transform (CQT) and support vector machines (SVMs). We present a collection of experiments using synthesized MIDI files and piano recordings, and compare the results with existing approaches.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Giovanni Costantini, Renzo Perfetti, Massimiliano Todisco,