Visual speech recognition using support vector machines
2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628) - Tập 2 - Trang 1093-1096 vol.2
Tóm tắt
In this paper we propose a visual speech recognition network based on support vector machines. Each word of the dictionary is described as a temporal sequence of visemes. Each viseme is described by a support vector machine, and the temporal character of speech is modeled by integrating the support vector machines as nodes into a Viterbi decoding lattice. Experiments conducted on a small visual speech recognition task show a word recognition rate on the level of the best rates previously reported, even without training the state transition probabilities in the Viterbi lattice and using very simple features. This proves the suitability of support vector machines for visual speech recognition.
Từ khóa
#Speech recognition #Support vector machines #Mouth #Hidden Markov models #Dictionaries #Viterbi algorithm #Lattices #Active shape model #Real time systems #InformaticsTài liệu tham khảo
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