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Speech Recognition by Composition of Weighted Finite Automata

Fernando C. N. Pereira·Michael D. Riley
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Abstract

We present a general framework based on weighted finite automata and weighted finite-state transducers for describing and implementing speech recognizers. The framework allows us to represent uniformly the information sources and data structures used in recognition, including context-dependent units, pronunciation dictionaries, language models and lattices. Furthermore, general but efficient algorithms can used for combining information sources in actual recognizers and for optimizing their application. In particular, a single composition algorithm is used both to combine in advance information sources such as language models and dictionaries, and to combine acoustic observations and information sources dynamically during recognition.

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BibTeXRIS

Fernando C. N. Pereira, Michael D. Riley. 1996-03-07. Speech Recognition by Composition of Weighted Finite Automata. https://arxiv.org/abs/cmp-lg/9603001

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