A two-channel training algorithm for hidden Markov model to identify visual speech elements
A novel two-channel algorithm is proposed in this paper for discriminative training of Hidden Markov Models (HMMs). It adjusts the symbol emission coefficients of an existing HMM to maximize the separable distance between a pair of confusable training samples. The method is applied to identify the v...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2009
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/90658 http://hdl.handle.net/10220/5843 |