A REAL−TIME LIP SYNC SYSTEM USING A GENETIC ALGORITHM FOR AUTOMATIC NEURAL NETWORK CONFIGURATION (ThuAmSS2)

نویسندگان

  • Goranka Zoric
  • Igor S. Pandzic
چکیده

In this paper we present a new method for mapping natural speech to lip shape animation in real time. The speech signal, represented by MFCC vectors, is classified into viseme classes using neural networks. The topology of neural networks is automatically configured using genetic algorithms. This eliminates the need for tedious manual neural network design by trial and error and considerably improves the viseme classification results. This method is suitable for real−time and offline applications.

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تاریخ انتشار 2005