Implementation and evaluation of an HMM-based Korean speech synthesis system

Development of a hidden Markov model (HMM)-based Korean speech synthesis system and its evaluation is described. Statistical HMM models for Korean speech units are trained with the hand-labeled speech database including the contextual information about phoneme, morpheme, word phrase, utterance, and break strength. The developed system produced speech with a fairly good prosody. The synthesized speech is evaluated and compared with that of our corpus-based unit concatenating Korean text-to-speech system. The two systems were trained with the same manually labeled speech database.
Publisher
IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
Issue Date
2006-03
Language
ENG
Citation

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E89D, pp.1116 - 1119

ISSN
0916-8532
URI
http://hdl.handle.net/10203/14731
Appears in Collection
EE-Journal Papers(저널논문)
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