DocumentCode :
1937823
Title :
An HMM-based speech synthesis system applied to English
Author :
Tokuda, Keiichi ; Heiga Zen ; Black, Alan W.
Author_Institution :
Nagoya Institute of Technology
fYear :
2002
fDate :
11-13 Sept. 2002
Firstpage :
227
Lastpage :
230
Abstract :
This paper describes an HMM-based speech synthesis system (HTS), in which the speech waveform is generated from HMM themselves, and applies it to English speech synthesis using the general speech synthesis architecture of Festival. Similarly to other data-driven speech synthesis approaches, HTS has a compact language dependent module: a list of contextual factors. Thus, it could easily be extended to other languages, though the first version of HTS was implemented for Japanese. The resulting run-time engine of HTS has the advantage of being small: less than 1 Mbyte, excluding text analysis part. Furthermore, HTS can easily change voice characteristics of synthesized speech by using a speaker adaptation technique developed for speech recognition. The relation between the HMM-based approach and other unit selection approaches is also discussed.
Keywords :
hidden Markov models; natural languages; speech synthesis; English language; Festival; HMM; HTS; contextual factors; language dependent module; speaker adaptation; speech synthesis system; speech waveform generation; Computer science; Databases; Engines; Hidden Markov models; High temperature superconductors; Natural languages; Parameter extraction; Runtime; Signal synthesis; Speech synthesis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Speech Synthesis, 2002. Proceedings of 2002 IEEE Workshop on
Print_ISBN :
0-7803-7395-2
Type :
conf
DOI :
10.1109/WSS.2002.1224415
Filename :
1224415
Link To Document :
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