Title :
Recent improvements of Probability Based Prosody Models for Unit Selection in concatenative Text-to-Speech
Author :
Zhang, Wei ; Gu, Liang ; Gao, Yuqing
Author_Institution :
IBM T. J. Watson Res. Center, Yorktown Heights, NY
Abstract :
The work presented in this paper is subsequent to the paper ldquoProbability Based Prosody Model for Unit Selectionrdquo 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.
Keywords :
natural language processing; probability; speech synthesis; concatenative text-to-speech; posterior probability; probability based prosody model; unit selection; Context modeling; Cost function; Databases; Decision trees; Information retrieval; Predictive models; Robustness; Runtime; Speech synthesis; Statistics; Posterior probability; Text-to-Speech (TTS); prosody model; unit selection;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-2353-8
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2009.4960449