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2M-BELEBELE: Highly Multilingual Speech and American Sign Language Comprehension Dataset

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arxiv 2412.08274 v3 pith:NWA6L3XE submitted 2024-12-11 cs.CL

Marta R. Costa-jussà , Bokai Yu , Pierre Andrews , Belen Alastruey , Necati Cihan Camgoz , Joe Chuang , Jean Maillard , Christophe Ropers
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Arina Turkantenko Carleigh Wood
This is my paper · ORCID
classification cs.CL
keywords comprehensiondatasetlanguagesignspeechamericanbelebelehighly
verification ladder T0 review T1 audit T2 compute T3 formal
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We introduce the first highly multilingual speech and American Sign Language (ASL) comprehension dataset by extending BELEBELE. Our dataset covers 74 spoken languages at the intersection of BELEBELE and FLEURS, and one sign language (ASL). We evaluate 2M-BELEBELE dataset for both 5-shot and zero-shot settings and across languages, the speech comprehension accuracy is ~ 2-3% average lower compared to reading comprehension.

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  1. Bridging Sign and Spoken Languages: Pseudo Gloss Generation for Sign Language Translation

    cs.CV 2025-05 conditional novelty 6.0 of 10

    LLM-generated pseudo glosses, reordered via weak video supervision, enable sign language translation that rivals gloss-supervised models while needing only 30 gloss examples.

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