Combination of hidden Markov models with dynamic time warping for speech recognition

We combine hidden Markov models of various topologies and nearest neighbor classification techniques in an exponential modeling framework with a model selection algorithm to obtain significant error rate reductions on an isolated word digit recognition task. This work is a preliminary investigation of large scale modeling techniques to be applied to large vocabulary continuous speech recognition.

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