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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© 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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