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State Duration Modeling for HMM-Based Speech Synthesis
Heiga ZEN Takashi MASUKO Keiichi TOKUDA Takayoshi YOSHIMURA Takao KOBAYASIH Tadashi KITAMURA
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2007/03/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Speech and Hearing
duration modeling, speech synthesis, hidden Markov model,
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This paper describes the explicit modeling of a state duration's probability density function in HMM-based speech synthesis. We redefine, in a statistically correct manner, the probability of staying in a state for a time interval used to obtain the state duration PDF and demonstrate improvements in the duration of synthesized speech.