A Harmonic-Based Biologically Inspired Approach to Monaural Speech Separation

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This letter proposes a computational auditory scene analysis (CASA) model for monaural speech separation. In this model, we integrate three biologically inspired approaches for: auditory spectrogram generation, analysis of its spectro-temporal content, and tracking its harmonic structure. In a top-down process, the estimated ideal binary mask (EIBM) is calculated using the spectral amplitude of the extracted spectrograms to enhance the harmonic filters for separation. Experimental results showed that our model outperformed the harmonic magnitude suppression technique in both signal-to-interference ratio and percentage of crosstalk. Moreover, the result is comparable with a current state-of-the-art system.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2012-09
Language
English
Article Type
Article
Keywords

SEGREGATION; TRACKING

Citation

IEEE SIGNAL PROCESSING LETTERS, v.19, no.9, pp.559 - 562

ISSN
1070-9908
DOI
10.1109/LSP.2012.2206382
URI
http://hdl.handle.net/10203/102771
Appears in Collection
EE-Journal Papers(저널논문)
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