A Support Vector Machine-Based Dynamic Network for Visual Speech Recognition Applications

• Main Authors: Gordan Mihaela, Kotropoulos Constantine, Pitas Ioannis
• Format: Article
• Language: English
• Published: SpringerOpen 2002-01-01
• Series: EURASIP Journal on Advances in Signal Processing
• Subjects: visual speech recognition; mouth shape recognition; visemes; phonemes; support vector machines; Viterbi lattice
• Online Access: http://dx.doi.org/10.1155/S1110865702207039
• ISSN: 1687-6172; 1687-6180

<p/> <p>Visual speech recognition is an emerging research field. In this paper, we examine the suitability of support vector machines for visual speech recognition. Each word is modeled as a temporal sequence of visemes corresponding to the different phones realized. One support vector machine is trained to recognize each viseme and its output is converted to a posterior probability through a sigmoidal mapping. To model the temporal character of speech, the support vector machines are integrated as nodes into a Viterbi lattice. We test the performance of the proposed approach on a small visual speech recognition task, namely the recognition of the first four digits in English. The word recognition rate obtained is at the level of the previous best reported rates.</p>