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A novel visual speech representation and HMM classification for visual speech recognition

Yu, Dahai and Ghita, Ovidiu and Sutherland, Alistair and Whelan, Paul F. (2009) A novel visual speech representation and HMM classification for visual speech recognition. Lecture Notes in Computer Science, 5414 . pp. 398-409. ISSN 1611-3349

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Abstract

This paper presents the development of a novel visual speech recognition (VSR) system based on a new representation that extends the standard viseme concept (that is referred in this paper to as Visual Speech Unit (VSU)) and Hidden Markov Models (HMM). The visemes have been regarded as the smallest visual speech elements in the visual domain and they have been widely applied to model the visual speech, but it is worth noting that they are problematic when applied to the continuous visual speech recognition. To circumvent the problems associated with standard visemes, we propose a new visual speech representation that includes not only the data associated with the articulation of the visemes but also the transitory information between consecutive visemes. To fully evaluate the appropriateness of the proposed visual speech representation, in this paper an extensive set of experiments have been conducted to analyse the performance of the visual speech units when compared with that offered by the standard MPEG-4 visemes. The experimental results indicate that the developed VSR application achieved up to 90% correct recognition when the system has been applied to the identification of 60 classes of VSUs, while the recognition rate for the standard set of MPEG-4 visemes was only in the range 62-72%.

Item Type:Article (Published)
Refereed:Yes
Uncontrolled Keywords:image analysis; Visual Speech Recognition; Visual Speech Unit; Viseme; EMPCA; HMM; Dynamic Time Warping
Subjects:UNSPECIFIED
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Publisher:Springer Verlag
Copyright Information:© 2009 Springer-Verlag The original publication is available at www.springerlink.com
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:14945
Deposited On:24 Sep 2013 16:10 by Alistair Sutherland. Last Modified 27 Oct 2017 10:28

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