A Set of Neural Tools for Human-Computer Interactions: Application to the Handwritten Character Recognition, and Visual Speech Recognition Problems

This paper presents a new technique of data coding and an associated set of homogenous processing tools for the development of Human Computer Interactions (HCI). The proposed technique facilitates the fusion of different sensorial modalities and simplifies the implementations. The coding takes into account the spatio-temporal nature of the signals to be processed in the framework of a sparse representation of data. Neural networks adapted to such a representation of data are proposed to perform the recognition tasks. Their development is illustrated by two examples: one of on-line handwritten character recognition; and the other of visual speech recognition.

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1. SUPÉLEC, Signal Processing and Neural Networks Team, Cesson Sévigné, France, , , , , , FR

   G. Vaucher, A. R. Baig & R. Séguier

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1. G. Vaucher
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2. A. R. Baig
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3. R. Séguier
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Vaucher, G., Baig, A. & Séguier, R. A Set of Neural Tools for Human-Computer Interactions: Application to the Handwritten Character Recognition, and Visual Speech Recognition Problems. NCA 9, 297–305 (2000). https://doi.org/10.1007/s005210070007

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• Issue Date: December 2000

• DOI: https://doi.org/10.1007/s005210070007

• Keywords: Human-machine interaction; Lipreading; On-line handwritten character recognition; Spatio-temporal coding; Spatio-temporal neural networks; Spatio-temporal patterns; Spiking neurons; Visual speech recognition