Reducing over-smoothness in HMM-based speech synthesis using exemplar-based voice conversion

Gia-Nhu Nguyen, Trung-Nghia Phung
2017 EURASIP Journal on Audio, Speech, and Music Processing  
Speech synthesis has been applied in many kinds of practical applications. Currently, state-of-the-art speech synthesis uses statistical methods based on hidden Markov model (HMM). Speech synthesized by statistical methods can be considered over-smooth caused by the averaging in statistical processing. In the literature, there have been many studies attempting to solve over-smoothness in speech synthesized by an HMM. However, they are still limited. In this paper, a hybrid synthesis between HMM
more » ... nthesis between HMM and exemplar-based voice conversion has been proposed. The experimental results show that the proposed method outperforms state-of-the-art HMM synthesis using global variance.
doi:10.1186/s13636-017-0113-5 fatcat:g7lr5o5llbdsljpundpi5mosza