Automatic intonation classification for speech training systems
نویسندگان
چکیده
A prosodic Hidden Markov model (HMM) based modality recognizer has been developed, which, after supra-segmental acoustic pre-processing, can perform clause and sentence boundary detection and modality (sentence type) recognition. This modality recognizer is adapted to carry out automatic evaluation of the intonation of the produced utterances in a speech training system for hearing-impaired persons or foreign language learners. The system is evaluated on utterances from normally-speaking persons and tested with speech-impaired (due to hearing problems) persons. To allow a deeper analysis, the automatic classification of the intonation is compared to subjective listening tests.
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