Multichannel speech dereverberation and separation with optimized combination of linear and non-linear filtering

In this paper, we propose a multichannel speech dereverberation and separation technique which is effective even when there are multiple speakers and each speaker's transfer function is time-varying due to fluctuation of the corresponding speaker's head. For robustness against fluctuation,...

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Bibliographic Details
Main Authors: Togami, M., Kawaguchi, Y., Takeda, R., Obuchi, Y., Nukaga, N.
Format: Conference Proceeding
Language:English
Subjects:
Covariance matrix
Dereverberation
Local Gaussian modeling
Microphones
Multichannel Wiener filter
Probabilistic logic
Reverberation
Speech
Speech separation
Transfer functions
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Summary:In this paper, we propose a multichannel speech dereverberation and separation technique which is effective even when there are multiple speakers and each speaker's transfer function is time-varying due to fluctuation of the corresponding speaker's head. For robustness against fluctuation, the proposed method optimizes linear filtering with non-linear filtering simultaneously from probabilistic perspective based on a probabilistic reverberant transfer-function model, PRTFM. PRTFM is an extension of the conventional time-invariant transfer-function model under uncertain conditions, and PRTFM can be also regarded as an extension of recently proposed blind local Gaussian modeling. The linear filtering and the non-linear filtering are optimized in MMSE (Minimum Mean Square Error) sense during parameter optimization. The proposed method is evaluated in a reverberant meeting room, and the proposed method is shown to be effective.
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2012.6288809