Use of Bimodal Coherence to Resolve Spectral Indeterminacy in Convolutive BSS
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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.
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Official URL: http://dx.doi.org/10.1007/978-3-642-15995-4_17
Abstract
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 (Paper) |
|---|---|
| Additional Information: | The original publication is available at http://www.springerlink.com |
| Divisions: | Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing |
| ID Code: | 7723 |
| Deposited By: | Symplectic Elements |
| Deposited On: | 09 Dec 2011 11:27 |
| Last Modified: | 08 Jun 2013 16:00 |
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