arXiv:2304.04068
Word-level Persian Lipreading Dataset
원문 초록
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 lipreading 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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Where Visual Speech Meets Language: VSP-LLM Framework for Efficient and Context-Aware Visual Speech Processing
Training Strategies for Improved Lip-reading
Leveraging Unimodal Self-Supervised Learning for Multimodal Audio-Visual Speech Recognition
Learning Audio-Visual Speech Representation by Masked Multimodal Cluster Prediction
Learn an Effective Lip Reading Model without Pains
Mutual Information Maximization for Effective Lip Reading
토론
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