Predicting intonational boundaries automatically from text: the ATIS domain
HLT '91 Proceedings of the workshop on Speech and Natural Language
A maximum entropy approach to natural language processing
Computational Linguistics
Learning rules for Chinese prosodic phrase prediction
SIGHAN '02 Proceedings of the first SIGHAN workshop on Chinese language processing - Volume 18
Automatic emphasis labeling for emotional speech by measuring prosody generation error
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
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Prosodic boundary prediction is the key to improving the intelligibility and naturalness of synthetic speech for a TTS system. This paper investigated the problem of automatic segmentation of prosodic word and prosodic phrase, which are two fundamental layers in the hierarchical prosodic structure of Mandarin Chinese. Maximum Entropy (ME) Model was used at the front end for both prosodic word and prosodic phrase prediction, but with different feature selection schemes. A multi-pass prediction approach was adopted. Besides, an error-driven rule-based modification module was introduced into the back end to amend the initial prediction. Experiments showed that this combined approach outperformed many other methods like C4.5 and TBL.