A fast match for continuous speech recognition using allophonic models
- 1 January 1992
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 1, 17-20 vol.1
- https://doi.org/10.1109/icassp.1992.225983
Abstract
In a large vocabulary real-time speech recognition system, there is a need for a fast method for selecting a list of candidate words from the vocabulary that match well with a given acoustic input. The authors describe a highly accurate fast acoustic match for continuous speech recognition. The algorithm uses allophonic models and efficient search techniques to select a set of candidate words. The allophonic models are derived by constructing decision trees that query the context in which each phone occurs to arrive at an allophone in a given context. The models for all the words in the vocabulary are arranged in a tree structure and efficient tree search algorithms are used to select a list of candidate words using these models. Using this method, the authors are able to obtain over 99% accuracy in the fast match for a continuous speech recognition task which has a vocabulary of 5000 words.Keywords
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