Use of Bimodal Coherence to Resolve Spectral Indeterminacy in Convolutive BSS
Liu, Q, Wang, W and Jackson, PJB (2010) Use of Bimodal Coherence to Resolve Spectral Indeterminacy in Convolutive BSS In: 9th International Conference on Latent Variable Analysis and Signal Separation (formerly the International Conference on Independent Component Analysis and Signal Separation), 2010-09-27 - 2010-09-30, St. Malo, France.
LiuWangJackson_LVA10.pdf - Accepted version Manuscript
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Recent studies show that visual information contained in visual speech can be helpful for the performance enhancement of audio-only blind source separation (BSS) algorithms. Such information is exploited through the statistical characterisation of the coherence between the audio and visual speech using, e.g. a Gaussian mixture model (GMM). In this paper, we present two new contributions. An adapted expectation maximization (AEM) algorithm is proposed in the training process to model the audio-visual coherence upon the extracted features. The coherence is exploited to solve the permutation problem in the frequency domain using a new sorting scheme. We test our algorithm on the XM2VTS multimodal database. The experimental results show that our proposed algorithm outperforms traditional audio-only BSS.
|Item Type:||Conference or Workshop Item (Conference Paper)|
|Divisions :||Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing|
|Date :||27 September 2010|
|Identification Number :||https://doi.org/10.1007/978-3-642-15995-4_17|
|Additional Information :||The original publication is available at http://www.springerlink.com|
|Depositing User :||Symplectic Elements|
|Date Deposited :||09 Dec 2011 11:27|
|Last Modified :||18 Feb 2015 14:34|
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