Single channel speech-music separation using matching pursuit and spectral masks

Grais, Emad Mounir and Erdoğan, Hakan (2011) Single channel speech-music separation using matching pursuit and spectral masks. In: IEEE 19th Conference on Signal Processing and Communications Applications Conference (SIU 2011), Antalya, Turkey


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A single-channel speech music separation algorithm based on matching pursuit (MP) with multiple dictionaries and spectral masks is proposed in this work. A training data for speech and music signals is used to build two sets of magnitude spectral vectors of each source signal. These vectors’ sets are called dictionaries, and the vectors are called atoms. Matching pursuit is used to sparsely decompose the magnitude spectrum of the observed mixed signal as a nonnegative weighted linear combination of the best atoms in the two dictionaries that match the mixed signal structure. The weighted sum of the resulting decomposition terms that include atoms from the speech dictionary is used as an initial estimate of the speech signal contribution in the mixed signal, and the weighted sum of the remaining terms for the music signal contribution. The initial estimate of each source is used to build a spectral mask that is used to reconstruct the source signals. Experimental results show that integrating MP with spectral mask gives good separation results.
Item Type: Papers in Conference Proceedings
Uncontrolled Keywords: Matching pursuit , Source separation , single channel source separation , speech music separation , speech processing
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Electronics
Faculty of Engineering and Natural Sciences
Depositing User: Emad Mounir Grais Girgis
Date Deposited: 23 Nov 2011 11:38
Last Modified: 26 Apr 2022 09:02

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