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Automatic Music Transcription using row weighted decompositions

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2 Author(s)
O'Hanlon, K. ; Centre for Digital Music, Queen Mary Univ. of London, London, UK ; Plumbley, M.D.

Automatic Music Transcription (AMT) seeks to understand a musical piece in terms of note activities. Matrix decomposition methods are often used for AMT, seeking to decompose a spectrogram over a dictionary matrix of note-specific template vectors. The performance of these methods can suffer due to the large harmonic overlap found in tonal musical spectra. We propose a row weighting scheme that transforms each spectrogram frame and the dictionary, with the weighting determined by the effective correlations in the decomposition. Experiments show improved AMT performance.

Published in:

Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on

Date of Conference:

26-31 May 2013

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