Phrase recognition in conversational speech using prosodic and phonemic information

In this paper, a new scheme for phrase recognition in conversational speech is proposed, in which prosodic and phonemic information processing are usefully combined. This approach is employed both to produce candidates of phrase boundaries and to discriminate phonemes. The fundamental frequency patterns of continuous utterances are statistically analyzed and the likelihood of the occurrence of a phrase boundary is calculated for every frame. At the same time, the likelihood of phonemic characteristics of each frame can be obtained using a hierarchical clustering method. These two scores, along with lexical and grammatical constraints, can be effectively utilized to develop a possible word sequences or a word lattices which correspond to the continuous speech utterances. Our preliminary experiment shows the feasibility of applying prosody for continuous speech recognition especially for conversational style utterances.