This paper describes a speech recognizer based on an HMM representation of quantized articulatory features and presents experimental results for its evaluation. Traditional schemes for HMM representation of speech have attempted to model a set of disjoint time segments. In order to create a more rob
Contextual vector quantization for speech recognition with discrete hidden Markov model
β Scribed by Qiang Huo; Chorkin Chan
- Publisher
- Elsevier Science
- Year
- 1995
- Tongue
- English
- Weight
- 541 KB
- Volume
- 28
- Category
- Article
- ISSN
- 0031-3203
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