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Department of Computational Linguistics Language, Technology and Accessibility

Paper SignCLIP accepted and presented at EMNLP 2024

Figure of SignCLIP: Connecting Text and Sign Language by Contrastive Learning

Our paperSignCLIP: Connecting Text and Sign Language by Contrastive Learning is accepted and presented at EMNLP 2024! SignCLIP re-purposes CLIP (Contrastive Language-Image Pretraining) to project spoken language text and sign language videos, two classes of natural languages of distinct modalities, into the same space. Thecode and a demo notebook are available.


Author team: Zifan Jiang, Gerard Sant, Amit Moryossef, Mathias Müller, Rico Sennrich, Sarah Ebling

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