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- W1699208071 abstract "This paper describes a new approach for automatic visible speech recognition based on hybrid hidden Markov models/neural networks. Suitable geometric features extracted from speaker's lip shapes are used to train the speech recognizer with nonsense sentences. First we describe the use of a geometrical-based model for visible speech and we outline a self-organising-map-based approach to determine the visual specific recognition units suitable for our speaker-dependent visible speech recognition task. Then we describe five automatic lipreading systems we developed according to different classification techniques: hidden Markov models, neural networks and hybrid hidden Markov models/neural networks. All these systems are tested on a connected letter recognition task. Finally, the performance comparison underlines that a hybrid hidden Markov models/neural networks based architecture is the most promising for automatic lipreading purposes." @default.
- W1699208071 created "2016-06-24" @default.
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- W1699208071 date "2002-11-27" @default.
- W1699208071 modified "2023-10-03" @default.
- W1699208071 title "Visible speech modelling and hybrid hidden Markov models/neural networks based learning for lipreading" @default.
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- W1699208071 doi "https://doi.org/10.1109/ijsis.1998.685470" @default.
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