An integrated approach to feature compensation combining particle filters and Hidden Markov Models for robust speech recognition
The performance of automatic speech recognition systems often degrades in adverse conditions where there is a mismatch between training and testing conditions. This is true for most modern systems which employ Hidden Markov Models (HMMs) to decode speech utterances. One strategy is to map the distor...
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| Format: | Others |
| Language: | en_US |
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Georgia Institute of Technology
2013
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| Online Access: | http://hdl.handle.net/1853/48982 |