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Hidden Markov Models

Categories: Speech


Author(s): Steve Renals

Hidden Markov modelling is a powerful stochastic approach to speech recognition. It is based on the assumption that the speech signal may be approximated by a first-order Markov process. Although this assumption is erroneous, their tractability, firm grounding in statistics and the existence of a powerful and provably convergent training algorithm have made hidden Markov models the dominant technique in speech recognition. Hidden Markov models are `hidden' since each state in the model does not necessarily correspond to a particular portion of the speech signal, but contains an output probability distribution over the input space.


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