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Prosody affects the naturalness and intelligibility of speech. However, automatic prosody prediction from text for Chinese speech synthesis is still a great challenge and the traditional conditional random fields (CRF) based method always heavily relies on feature engineering. In this paper, we propose to use neural networks to predict prosodic boundary labels directly from Chinese characters without...
This paper presents a deep neural network (DNN) approach for head motion synthesis, which can automatically predict head movement of a speaker from his/her speech. Specifically, we realize speech-to-head-motion mapping by learning a DNN from audio-visual broadcast news data. We first show that a generatively pre-trained neural network significantly outperforms a conventional randomly initialized network...
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