Recent improvements of Probability Based Prosody Models for Unit Selection in concatenative Text-to-Speech

Authors:
Wei Zhang;Liang Gu;Yuqing Gao
Affiliations:
IBM T. J. Watson Research Center, Yorktown Heights, NY 10598 USA;IBM T. J. Watson Research Center, Yorktown Heights, NY 10598 USA;IBM T. J. Watson Research Center, Yorktown Heights, NY 10598 USA
Venue:
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Year:
2009

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Abstract

The work presented in this paper is subsequent to the paper “Probability Based Prosody Model for Unit Selection” which was published in ICASSP'2004. In the improved probability prosody model for corpus based concatenative Text-to-Speech (TTS), likelihood is replaced with posterior probability in the cost functions which conduct the following step, unit selection. Objective and subjective experiments show that posterior probability has obvious advantages over likelihood on robustness, flexibility and overall quality.