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Audio-visual Convolutive Blind Source Separation

Liu, Q, Wang, W and Jackson, P (2010) Audio-visual Convolutive Blind Source Separation In: Sensor Signal Processing for Defence, 2010-09-29 - 2010-09-30, London, UK.

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We present a novel method for speech separation from their audio mixtures using the audio-visual coherence. It consists of two stages: in the off-line training process, we use the Gaussian mixture model to characterise statistically the audio-visual coherence with features obtained from the training set; at the separation stage, likelihood maximization is performed on the independent component analysis (ICA)-separated spectral components. To address the permutation and scaling indeterminacies of the frequency-domain blind source separation (BSS), a new sorting and rescaling scheme using the bimodal coherence is proposed.We tested our algorithm on the XM2VTS database, and the results show that our algorithm can address the permutation problem with high accuracy, and mitigate the scaling problem effectively.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors : Liu, Q, Wang, W and Jackson, P
Date : 29 September 2010
DOI : 10.1049/ic.2010.0225
Contributors :
Additional Information : © 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User : Symplectic Elements
Date Deposited : 12 Dec 2012 15:32
Last Modified : 06 Jul 2019 05:10

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