Sign Language Translation from Instructional Videos
This work addresses the need for better translation tools for deaf and hard-of-hearing individuals, but it is incremental as it applies existing methods to a new dataset.
The paper tackles the problem of sign language translation from instructional videos by providing the first baseline results on the large and broad How2Sign dataset, achieving a BLEU score of 8.03.
The advances in automatic sign language translation (SLT) to spoken languages have been mostly benchmarked with datasets of limited size and restricted domains. Our work advances the state of the art by providing the first baseline results on How2Sign, a large and broad dataset. We train a Transformer over I3D video features, using the reduced BLEU as a reference metric for validation, instead of the widely used BLEU score. We report a result of 8.03 on the BLEU score, and publish the first open-source implementation of its kind to promote further advances.