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- W4252331534 abstract "The use of hidden Markov models for speech recognition has become predominant in the last several years, as evidenced by the number of published papers and talks at major speech conferences. The reasons this method has become so popular are the inherent statistical (mathematically precise) framework; the ease and availability of training algorithms for cstimating the parameters of the models from finite training sets of speech data; the flexibility of the resulting recognition system in which one can easily change the size, type, or architecture of the models to suit particular words, sounds, and so forth; and the ease of implementation of the overall recognition system. In this expository article, we address the role of statistical methods in this powerful technology as applied to speech recognition and discuss a range of theoretical and practical issues that are as yet unsolved in terms of their importance and their effect on performance for different system implementations." @default.
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- W4252331534 date "1991-08-01" @default.
- W4252331534 modified "2023-10-16" @default.
- W4252331534 title "Hidden Markov Models for Speech Recognition" @default.
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- W4252331534 doi "https://doi.org/10.1080/00401706.1991.10484833" @default.
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