Title :
An optimization algorithm of independent mean and variance parameter tying structures for HMM-based speech synthesis
Author :
Takaki, Shinji ; Oura, Keiichiro ; Nankaku, Yoshihiko ; Tokuda, Keiichi
Author_Institution :
Dept. of Comput. Sci. & Eng., Nagoya Inst. of Technol., Nagoya, Japan
Abstract :
This paper proposes a technique for constructing independent parameter tying structures of mean and variance in HMM based speech synthesis. Conventionally, mean and variance parameters are assumed to have the same tying structure. However, it has been reported that a clustering technique of mean vectors while tying all variance matrices improves the quality of synthesized speech. This indicates that mean and variance parameters should have different optimal tying structures. In the proposed technique, the decision trees for mean and variance parameters are simultaneously grown by taking into account the dependency on mean and variance parameters. Experimental results show that the proposed technique outperforms the conventional one.
Keywords :
hidden Markov models; matrix algebra; optimisation; speech synthesis; HMM-based speech synthesis; decision trees; optimization algorithm; variance matrices; variance parameter; Additives; Context; Context modeling; Decision trees; Hidden Markov models; Speech; Speech synthesis; context clustering; decision trees; hidden Markov models; speech synthesis;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
Conference_Location :
Prague
Print_ISBN :
978-1-4577-0538-0
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2011.5947404