Abstract
We present lipreading using recurrent neural prediction model. Lipreading copes with time-series data like speech recognition. Therefore, many traditional methods use Hidden Markov Model (HMM) as the classifier for lipreading. However, in recent years, a speech recognition method using Recurrent Neural Prediction Model (RNPM) is proposed, and good result is reported. It is expected that RNPM also gives the good result for lipreading, because lipreading has the similar properties with speech recognition. The effectiveness of the proposed method is confirmed by using 8 words captured from 5 persons. In addition, the comparison with HMM is performed. It is confirmed that the comparable performance is obtained.
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References
Rogozan, A., Deléglise, P.: Adaptive fusion of acoustic and visual sources for automatic speech recognition. Speech Communication 26(1-2), 149–161 (1998)
Potamianos, G., Neti, C., Iyengar, G., Helmuth, E.: Large-Vocabulary Audio-Visual Speech Recognition by Machines and Humans. In: Proc. Eurospeech (2001)
Iwano, K., Tamura, S., Furui, S.: Bimodal Speech Recognition Using Lip Movement Measured by Optical-Flow Analysis. In: Proceedings International Workshop on Hands-Free Speech Communication, pp. 187–190 (2001)
Mase, K., Pentland, A.: Lipreading by optical flow. Systems and Computers in Japan 22(6), 67–76 (1991)
Uchiyama, T., Takahashi, H.: Speech Recognition Using Recurrent Neural Prediction Model. IEICE Transactions on Information and Systems D-II J83-DII(2), 776–783 (2000) (in Japanese)
Lucas, B.D., Kanade, T.: An Iterative Image Registration Technique with an Application to Stereo Vision. In: Proceedings of Imaging Understanding Workshop, pp. 121–130 (1981)
Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification, 2nd edn. John Wiley & Sons, Inc., Chichester (2001)
Jordan, M.: Serial order: A Parallel Distributed Processing Approach, Technical report ICS, no.8604 (1986)
Elman, J.L.: Finding structure in time. Cognitive Science 14, 179–211 (1990)
Rabiner, L.: A tutorial on Hidden Markov Models and selected applications in speech recognition. Proc. of IEEE 77(2), 257–286 (1989)
Huang, X.D., Ariki, Y., Jack, M.A.: Hidden Markov Models for Speech Recognition. Edinburgh Univ. Press (1990)
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© 2004 Springer-Verlag Berlin Heidelberg
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Tsunekawa, T., Hotta, K., Takahashi, H. (2004). Lipreading Using Recurrent Neural Prediction Model. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30126-4_50
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DOI: https://doi.org/10.1007/978-3-540-30126-4_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23240-7
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