【摘 要】
：
Deep Neural Network(DNN),which can model hierarchical and complex relationship between input and output layer has recently been applied in speech synthesis.
【出 处】
：
第七届国际博士生论坛暨青年教师发展研讨会
论文部分内容阅读
Deep Neural Network(DNN),which can model hierarchical and complex relationship between input and output layer has recently been applied in speech synthesis.However,it is remained uncertain why DNN outperform traditional HMM based synthesis.This paper describes several implementation details of DNN-based speech synthesis system and compares different impacting factors,e.g,F0 modeling method and adding BAP feature.DNN-based system are further investigated and in particular Continuous F0 HMM(CF-HMM)is taken as the baseline to compare with DNN-based system,as it has more similar input and output features with DNN-based system.
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