Summary of Scaling Sign Language Translation, by Biao Zhang and Garrett Tanzer and Orhan Firat
Scaling Sign Language Translation
by Biao Zhang, Garrett Tanzer, Orhan Firat
First submitted to arxiv on: 16 Jul 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper explores the challenge of translating information from sign language in videos to spoken language in text. Existing studies have made progress but are limited to specific domains or languages. To overcome these limitations, this study scales up pre-training data, model size, and translation directions. The researchers use a combination of noisy YouTube video data, parallel text corpora, and augmented SLT data to train the models. They unify different tasks under an encoder-decoder architecture and initialize the SLT model with pre-trained (m/By)T5 models across various sizes. Results show that scaling up data and models improves performance on sign language translation tasks, including zero-shot translations. The study also finetunes the pretrained models on 5 downstream open-domain benchmarks covering 5 sign languages, achieving substantial quality improvements over vanilla baselines and surpassing previous state-of-the-art results. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps computers understand sign language in videos and translate it into spoken language. It’s like a superpower for people who are deaf or hard of hearing! The researchers tried to make the computer better at this task by giving it more training data, bigger models, and the ability to learn from different languages. They also used special techniques to help the computer understand sign language better. The results show that the computer is now much better at translating sign language into spoken language, which can be really helpful for people who need it. |
Keywords
» Artificial intelligence » Encoder decoder » T5 » Translation » Zero shot
