Robust parametric modeling of durations in hidden Markov models

A major weakness of conventional hidden Markov models is that they implicitly model state durations by a geometric distribution, which is usually inappropriate. This paper presents a modified Viterbi algorithm that, by incorporating proper state and word duration modeling, significantly reduces the string error rate of the conventional Viterbi algorithm for a speaker-independent, connected-digit string task. The algorithm has essentially the same computational requirements of the conventional Viterbi algorithm.