Use of prosodic information to integrate acoustic and linguistic knowledge in continuous Mandarin speech recognition with very large vocabulary

This paper presents a new approach to use prosodic information for the integration of acoustic and linguistic knowledge in continuous Mandarin speech with very large vocabulary. Since the overhead computation incurred from unification of search space is confined to the syllable boundaries, the use of prosodic information to reduce the syllable boundary hypotheses as well as the syllable matching length is shown to be effective. The inherent complexity with the very large vocabulary is also reduced by the use of phrase boundary hypotheses conjectured via the phrase-final lengthening. Experimental results show a 47.2% recognition time save with only 5.67% error rate increase using the syllable and phrase boundary hypotheses conjectured from prosodic information.