most citedYouTube-SL-25: A Large-Scale, Open-Domain Multilingual Sign Language Parallel Corpus

2 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2024

FLEURS-ASL: Including American Sign Language in Massively Multilingual Multitask Evaluation

Garrett Tanzer

Sign language translation has historically been peripheral to mainstream machine translation research. In order to help converge the fields, we introduce FLEURS-ASL, an extension o…

cs.CL2024

Fingerspelling within Sign Language Translation

Garrett Tanzer

Fingerspelling poses challenges for sign language processing due to its high-frequency motion and use for open-vocabulary terms. While prior work has studied fingerspelling recogni…

cs.CV2024

FSboard: Over 3 million characters of ASL fingerspelling collected via smartphones

Manfred Georg, Garrett Tanzer, Saad Hassan +5

Progress in machine understanding of sign languages has been slow and hampered by limited data. In this paper, we present FSboard, an American Sign Language fingerspelling dataset…

cs.CL2024

Scaling Sign Language Translation

Biao Zhang, Garrett Tanzer, Orhan Firat

Sign language translation (SLT) addresses the problem of translating information from a sign language in video to a spoken language in text. Existing studies, while showing progres…

cs.CL20242 cited

YouTube-SL-25: A Large-Scale, Open-Domain Multilingual Sign Language Parallel Corpus

Garrett Tanzer, Biao Zhang

Even for better-studied sign languages like American Sign Language (ASL), data is the bottleneck for machine learning research. The situation is worse yet for the many other sign l…

cs.CL2024

Reconsidering Sentence-Level Sign Language Translation

Garrett Tanzer, Maximus Shengelia, Ken Harrenstien +1

Historically, sign language machine translation has been posed as a sentence-level task: datasets consisting of continuous narratives are chopped up and presented to the model as i…