International Conference on Computer and Knowledge Engineering

Home / 12th International Conference on Computer and Knowledge Engineering

Word-level Persian Lipreading Dataset

Authors :

Javad Peymanfard¹ Ali Lashini² Samin Heydarian³ Hossein Zeinali⁴ Nasser Mozayani⁵

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.