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Research on Visual Speech Recognition Based on Local Binary Pattern and Stacked Sparse Autoencoder

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Human Systems Engineering and Design (IHSED 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 876))

Abstract

Lip feature extraction from human mouth image plays an essential role in visual speech recognition applications. This paper presents a lip feature extraction algorithm based on Local Binary Patterns (LBP) and Stacked Sparse Autoencoders (SSAE). First, LBP texture features are extracted from lip images. Then SSAE uses greedy unsupervised learning to extract high-level features. At last, we improve the performance of overall system by fine-tuning and input the extracted features into the Softmax classifier. Compared with traditional methods, the model proposed in this paper has higher classification accuracy and more applicability.

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Acknowledgements

The research was supported by the National Natural Science Foundation of China (61571013), by the Beijing Natural Science Foundation of China (4143061). The authors thank all the partners and the participants in the experiment for their help, by the Science and Technology Development Program of Beijing Municipal Education Commission (KM201710009003) and by the Great Wall Scholar Reserved Talent Program of North China University of Technology (NCUT2017XN018013).

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Authors and Affiliations

  1. School of Electronic and Information Engineering, North China University of Technology, Beijing, 100144, China

    Yuanyao Lu, Ke Gu & Shan He

Authors
  1. Yuanyao Lu
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  2. Ke Gu
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  3. Shan He
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Corresponding author

Correspondence to Yuanyao Lu .

Editor information

Editors and Affiliations

  1. Institute for Advanced Systems Engineering, University of Central Florida, Orlando, FL, USA

    Tareq Ahram

  2. University of Central Florida, Orlando, FL, USA

    Waldemar Karwowski

  3. Université de Reims Champagne-Ardenne, Reims, France

    Redha Taiar

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Lu, Y., Gu, K., He, S. (2019). Research on Visual Speech Recognition Based on Local Binary Pattern and Stacked Sparse Autoencoder. In: Ahram, T., Karwowski, W., Taiar, R. (eds) Human Systems Engineering and Design. IHSED 2018. Advances in Intelligent Systems and Computing, vol 876. Springer, Cham. https://doi.org/10.1007/978-3-030-02053-8_165

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