On hidden Markov model and dynamic time warping for speech recognition - A unified tutorial view.

This paper provides a unified theoretical view on the dynamic time warping (DTW) and the hidden Markov model (HMM) techniques for speech recognition problems. The application of hidden Markov models in speech recognition will be discussed. We then show that the conventional dynamic time warping algorithm with linear predictive (LP) signal modeling and distortion measurements can be formulated in a strictly statistical framework.