title: Segmenting speech using dynamic programming.
abstract: Speech is modeled as a Markov chain. Scoring is developed to convert observations of the speech signal into estimated probabilities of the locations of segment boundaries. Dynamic programming is then used to compute a most-probable segmentation for the speech. The process automatically adjusts to speakers and incorporates a priori information in a probabilistic and systemic fashion. The performance of the algorithm appears to be state-of-the-art, independent of speaker.
mesh_terms: D003201:Computers; D006801:Humans; D008390:Markov Chains; D008722:Methods; D008960:Models, Psychological; D010700:Phonetics; D011336:Probability; D013067:Speech Perception