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- W2125157818 abstract "We introduce a novel mechanism for incorporating articulatory dynamics into speech recognition with the theory of task dynamics. This system reranks sentence-level hypotheses by the likelihoods of their hypothetical articulatory realizations which are derived from relationships learned with aligned acoustic/articulatory data. Experiments compare this with two baseline systems, namely an acoustic hidden Markov model and a dynamic Bayes network augmented with discretized representations of the vocal tract. Our system based on task dynamics reduces word-error rates significantly by 10.2% relative to the best baseline models." @default.
- W2125157818 created "2016-06-24" @default.
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- W2125157818 date "2010-07-11" @default.
- W2125157818 modified "2023-09-28" @default.
- W2125157818 title "Correcting Errors in Speech Recognition with Articulatory Dynamics" @default.
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