Abstract
This paper presents a system that recognizes the lip movement for lip-reading system. Four lip gestures are recognized: rounded open, wide open, small open and closed. These gestures are used to describe visually the speech. Firstly, we detect the mouth region from frame using Viola–Jones algorithm. Then, we use DCT to extract the mouth features. The recognition is performed by a HMM which achieves a high performance of 84.99%.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Makhlouf, A., Lazli, L., Bensaker, B.: Evolutionary structure of hidden Markov models for audio-visual Arabic speech recognition. Int. J. Signal Imaging Syst. Eng. 9, 55–66 (2016)
Petajan, E.D.: Automatic lipreading to enhance speech recognition (speech reading) (1984)
Puviarasan, N., Palanivel, S.: Lip reading of hearing impaired persons using HMM. Expert Syst. Appl. 38, 4477–4481 (2011)
Shin, J., Lee, J., Kim, D.: Real-time lip reading system for isolated Korean word recognition. Pattern Recogn. 44, 559–571 (2011)
Petridis, S., Li, Z., Pantic, M.: End-to-end visual speech recognition with LSTMs. In: 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2592–2596. IEEE (2017)
Wang, Y.Q.: An analysis of the Viola-Jones face detection algorithm. Image Process. Line 4, 128–148 (2014)
Addarrazi, I., Satori, H., Satori, K.: Amazigh audiovisual speech recognition system design. In: 2017 Intelligent Systems and Computer Vision (ISCV), pp. 1–5. IEEE (2017)
Satori, H., ElHaoussi, F.: Investigation Amazigh speech recognition using CMU tools. Int. J. Speech Technol. 17, 235–243 (2014)
Mohamed, H., Hassan, S., Ouissam, Z., Khalid, S., Naouar, L.: Interactive voice response server voice network administration using hidden Markov model speech recognition system. In: 2018 Second World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4), 16–21. IEEE (2018)
Zealouk, O., Satori, H., Hamidi, M., Laaidi, N., Satori, K.: Vocal parameters analysis of smoker using Amazigh language. Int. J. Speech Technol. 21, 85–91 (2018)
Ilham, A., Hassan, S., Khalid, S.: Building a first Amazigh database for automatic audiovisual speech recognition system. In: Proceedings of the 2nd International Conference on Smart Digital Environment ACM, pp. 94–99 (2018)
Dalka, P., Czyzewski, A.: Human-computer interface based on visual lip movement and gesture recognition. IJCSA 7, 124–139 (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Addarrazi, I., Satori, H., Satori, K. (2020). Lip Movement Modeling Based on DCT and HMM for Visual Speech Recognition System. In: Bhateja, V., Satapathy, S., Satori, H. (eds) Embedded Systems and Artificial Intelligence. Advances in Intelligent Systems and Computing, vol 1076. Springer, Singapore. https://doi.org/10.1007/978-981-15-0947-6_38
Download citation
DOI: https://doi.org/10.1007/978-981-15-0947-6_38
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-0946-9
Online ISBN: 978-981-15-0947-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)