We survey the use of weighted finite-state transducers (WFSTs) in speech recognition. We show that WFSTs provide a common and natural representation for hidden Markov models (HMMs), context-dependency, pronunciation dictionaries, grammars, and alternative recognition outputs. Furthermore, general tr
โฆ LIBER โฆ
Learning a Discriminative Weighted Finite-State Transducer for Speech Recognition
โ Scribed by Lehr, M.; Shafran, I.
- Book ID
- 114599474
- Publisher
- Institute of Electrical and Electronics Engineers
- Year
- 2011
- Tongue
- English
- Weight
- 638 KB
- Volume
- 19
- Category
- Article
- ISSN
- 1558-7916
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