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arXiv · 2406.00038

ViSpeR: Multilingual Audio-Visual Speech Recognition

Sanath Narayan·Yasser Abdelaziz Dahou Djilali·Ankit Singh·Eustache Le Bihan·Hakim Hacid
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Abstract

This work presents an extensive and detailed study on Audio-Visual Speech Recognition (AVSR) for five widely spoken languages: Chinese, Spanish, English, Arabic, and French. We have collected large-scale datasets for each language except for English, and have engaged in the training of supervised learning models. Our model, ViSpeR, is trained in a multi-lingual setting, resulting in competitive performance on newly established benchmarks for each language. The datasets and models are released to the community with an aim to serve as a foundation for triggering and feeding further research work and exploration on Audio-Visual Speech Recognition, an increasingly important area of research. Code available at \href{https://github.com/YasserdahouML/visper}{https://github.com/YasserdahouML/visper}.

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Sanath Narayan, Yasser Abdelaziz Dahou Djilali, Ankit Singh, Eustache Le Bihan, Hakim Hacid. 2024-05-27. ViSpeR: Multilingual Audio-Visual Speech Recognition. https://arxiv.org/abs/2406.00038

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