2002 WeightedFiniteStateTransiSpRecog
- (Mohri et al., 2001) ⇒ Mehryar Mohria, Fernando Pereirab, and Michael Rileya. (2002). “Weighted Finite-state Transducers in Speech Recognition.” In: Computer Speech & Language, 16(1). doi:10.1006/csla.2001.0184
Subject Headings: Weighted Finite-State Transducer
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Abstract
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 transducer operations combine these representations flexibly and efficiently. Weighted determinization and minimization algorithms optimize their time and space requirements, and a weight pushing algorithm distributes the weights along the paths of a weighted transducer optimally for speech recognition.
As an example, we describe a North American Business News (NAB) recognition system built using these techniques that combines the HMMs, full cross-word triphones, a lexicon of 40 000 words, and a large trigram grammar into a single weighted transducer that is only somewhat larger than the trigram word grammar and that runs NAB in real-time on a very simple decoder. In another example, we show that the same techniques can be used to optimize lattices for second-pass recognition. In a third example, we show how general automata operations can be used to assemble lattices from different recognizers to improve recognition performance.
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| Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
|---|---|---|---|---|---|---|---|---|---|---|
| 2002 WeightedFiniteStateTransiSpRecog | Mehryar Mohria Fernando Pereirab Michael Rileya | Weighted Finite-state Transducers in Speech Recognition | http://www.sciencedirect.com/science/article/pii/S0885230801901846 |