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A large-vocabulary, continuous-speech system, called DECIPHER, which is based on a hidden Markov model (HMM) approach and is designed to achieve high word accuracy in a speaker-independent mode is described. The results of a series of experiments that test acoustic and phonological adaptation of the DECIPHER system to the pronunciations of a single speaker in a speaker-dependent task are presented. Estimating the probabilities of alternative pronunciations and speaker-dependent phonology are discussed.>
Cohen et al. (Wed,) studied this question.