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12th International Conference on Computer and Knowledge Engineering
Word-level Persian Lipreading Dataset
Authors :
Javad Peymanfard
1
Ali Lashini
2
Samin Heydarian
3
Hossein Zeinali
4
Nasser Mozayani
5
1- School of Computer Engineering Iran University of Science and Technology, Tehran, Iran
2- School of Computer Engineering Iran University of Science and Technology, Tehran, Iran
3- School of Computer Engineering Iran University of Science and Technology, Tehran, Iran
4- Department of Computer Engineering Amirkabir University of Technology, Tehran, Iran
5- School of Computer Engineering Iran University of Science and Technology, Tehran, Iran
Keywords :
Lip-reading،Persian dataset،audio-visual speech recognition
Abstract :
Lip-reading has made impressive progress in recent years, driven by advances in deep learning. Nonetheless, the prerequisite such advances is a suitable dataset. This paper provides a new in-the-wild dataset for Persian word-level lip reading containing 244,000 videos from approximately 1,800 speakers. We evaluated the state-of-the-art method in this field and used a novel approach for word-level lip reading. In this method, we used the AV-Hubert model for feature extraction and obtained significantly better performance on our dataset.
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