التفاصيل البيبلوغرافية
| العنوان: |
ViSpeR: Multilingual Audio-Visual Speech Recognition |
| المؤلفون: |
Narayan, Sanath, Djilali, Yasser Abdelaziz Dahou, Singh, Ankit, Bihan, Eustache Le, Hacid, Hakim |
| سنة النشر: |
2024 |
| المجموعة: |
Computer Science |
| مصطلحات موضوعية: |
Computer Science - Computation and Language, Computer Science - Artificial Intelligence |
| الوصف: |
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}. |
| نوع الوثيقة: |
Working Paper |
| URL الوصول: |
http://arxiv.org/abs/2406.00038 |
| رقم الانضمام: |
edsarx.2406.00038 |
| قاعدة البيانات: |
arXiv |