Speech Recognition by Composition of Weighted Finite Automata
<|reference_start|>Speech Recognition by Composition of Weighted Finite Automata: 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.<|reference_end|>
@article{pereira1996speech,
    title={Speech Recognition by Composition of Weighted Finite Automata},
    author={Fernando C. N. Pereira and Michael D. Riley (AT&T Research)},
    journal={arXiv preprint arXiv:cmp-lg/9603001},
    year={1996},
    archivePrefix={arXiv},
    eprint={cmp-lg/9603001},
    primaryClass={cmp-lg cs.CL}
}