【摘 要】
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This paper presents a neural network approach for speech-driven head motion synthesis,which can automatically predict a speakers head movement from his/her speech.Specifically,we realize speech-to-hea
【出 处】
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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
This paper presents a neural network approach for speech-driven head motion synthesis,which can automatically predict a speakers head movement from his/her speech.Specifically,we realize speech-to-headmotion mapping by learning a multi-layer perceptron from audio-visual broadcast news data.First,we show that a generatively pre-trained neural network significantly outperforms a randomly initialized network and the Hidden Markov Model(HMM)approach.
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