Incorporating Phase Information for Source Separation via Spectrogram Factorization
Parry, R.M.
Essa, I.
Coll. of Comput., Georgia Inst. of Technol., Atlanta, GA;
This paper appears in: Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
Publication Date: 15-20 April 2007
Volume: 2,
On page(s): II-661-II-664
Location: Honolulu, HI,
ISSN: 1520-6149
ISBN: 1-4244-0727-3
INSPEC Accession Number: 9497202
Digital Object Identifier: 10.1109/ICASSP.2007.366322
Current Version Published: 2007-06-04
Abstract
Spectrogram factorization methods have been proposed for single channel source separation and audio analysis. Typically, the mixture signal is first converted into a time-frequency representation such as the short-time Fourier transform (STFT). The phase information is thrown away and this spectrogram matrix is then factored into the sum of rank-one source spectrograms. This approach incorrectly assumes the mixture spectrogram is the sum of the source spectrograms. In fact, the mixture spectrogram depends on the phase of the source STFTs. We investigate the consequences of this common assumption and introduce an approach that leverages a probabilistic representation of phase to improve the separation results
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