Word-level Persian Lipreading Dataset
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Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 12 of its 23 references that are in the map. First posted on arXiv 8 Apr 2023.
Builds on
12 of 23 references.
References · 12
- 2018LRS3-TED: a large-scale dataset for visual speech recognitioncited by 301
- 2016Lip Reading Sentences in the Wildcited by 226
- 2017S3FD: Single Shot Scale-invariant Face Detectorcited by 142
- 2021Is Someone Speaking? Exploring Long-term Temporal Features for Audio-visual Active Speaker Detectioncited by 110
- 2020Lipreading using Temporal Convolutional Networkscited by 98
- 2019AVA-ActiveSpeaker: An Audio-Visual Dataset for Active Speaker Detectioncited by 81
- 2017Combining Residual Networks with LSTMs for Lipreadingcited by 66
- 2018LRW-1000: A Naturally-Distributed Large-Scale Benchmark for Lip Reading in the Wildcited by 51
- 2020Towards Practical Lipreading with Distilled and Efficient Modelscited by 44
- 2022Distinguishing Homophenes Using Multi-Head Visual-Audio Memory for Lip Readingcited by 39
- 2022A Multimodal German Dataset for Automatic Lip Reading Systems and Transfer Learningcited by 8
- 2021Lip reading using external viseme decodingcited by 5
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Citing papers per year: 2023: 1; 2024: 0; 2025: 1.
2 papers.