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- W2375877876 abstract "Speech is produced by co-operation of all speech organs, and there are inherent relations between speech and movement of speech organs. To predict viseme parameters from speech using neural network, input speech parameters selection, time domain and structure of neural network were studied. Experiment results show that LPC coefficient plus short time energy are superior to other speech parameters, forward co-articulation is more server than backward co-articulation, and a delay feedback can improve the forward neural network performance. Considering experiments were based on unlimited vocabulary and continuous speech, the 0.0114 mean square error (MSE) is quite promising." @default.
- W2375877876 created "2016-06-24" @default.
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- W2375877876 date "2005-01-01" @default.
- W2375877876 modified "2023-09-23" @default.
- W2375877876 title "Predicting Viseme Parameters from Speech Based on Neural Network" @default.
- W2375877876 hasPublicationYear "2005" @default.
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