Note onset detection for the transcription of polyphonic piano music

Note onset detection for the transcription of polyphonic piano music

erschienen 27.05.09 Technical Report, Institute of Computer Science, University of Augsburg, May 2009

ABSTRACT

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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