Audio-Visual Sound Separation Using Hidden Markov Models
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Casey, Michael A. and Hershey, J.. 2002. 'Audio-Visual Sound Separation Using Hidden Markov Models'. In: Advances in Neural Information Processing Systems. UNDEFINED 1/1/2002. [Conference or Workshop Item]
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Conference or Workshop Item (Paper) |
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| Additional Information: |
Originalty: presents a major advancement on the state-of-the-art for multi-speaker audio source separation in a single channel. Also, it is one of the first major publications introducing the joint audio-visual approach to separating individuals' speech from a mixture. Rigour: Bayesian modeling yields an Expectation Maximization algorithm to solve inference in factorial (coupled) hidden Markov models for individual speakers using audio-visual features. Significance: The NIPS acceptance rate is consistently below 30%, the conference is a primary source for machine learning and audio. Funded by Mitsubishi Electric Research, this research is used in their general audio products. |
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1/1/2002 |
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| Item ID: |
965 |
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| Date Deposited: |
12 Mar 2009 15:41 |
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| Last Modified: |
20 Jun 2017 09:43 |
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