Abstract
This paper presents the results of the First WMT Shared Task on Sign Language Translation (WMT-SLT22). This shared task is concerned with automatic translation between signed and spoken2 languages. The task is novel in the sense that it requires processing visual information (such as video frames or human pose estimation) beyond the well-known paradigm of text-to-text machine translation (MT). The task featured two tracks, translating from Swiss German Sign Language (DSGS) to German and vice versa. Seven teams participated in this first edition of the task, all submitting to the DSGS-to-German track. Besides a system ranking and system papers describing state-of-the-art techniques, this shared task makes the following scientific contributions: novel corpora, reproducible baseline systems and new protocols and software for human evaluation. Finally, the task also resulted in the first publicly available set of system outputs and human evaluation scores for sign language translation.
Original language | English |
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Title of host publication | WMT 2022 - 7th Conference on Machine Translation, Proceedings of the Conference |
Publisher | Association for Computational Linguistics |
Pages | 744-772 |
Number of pages | 29 |
ISBN (Electronic) | 9781959429296 |
State | Published - 2022 |
Event | 7th Conference on Machine Translation, WMT 2022 - Abu Dhabi, United Arab Emirates Duration: 7 Dec 2022 → 8 Dec 2022 |
Publication series
Name | Conference on Machine Translation - Proceedings |
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ISSN (Electronic) | 2768-0983 |
Conference
Conference | 7th Conference on Machine Translation, WMT 2022 |
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Country/Territory | United Arab Emirates |
City | Abu Dhabi |
Period | 7/12/22 → 8/12/22 |
Bibliographical note
Publisher Copyright:© 2022 Association for Computational Linguistics.
Funding
This shared task was funded by the European Association for Machine Translation (EAMT) and by Microsoft AI for Accessibility. We are grateful for their support which enabled us to provide test data, human evaluation and interpretation in International Sign during the WMT conference. The organizing committee further acknowledge funding from the following projects: the EU Horizon 2020 projects EASIER (grant agreement number 101016982) and SignON (101017255), the Swiss Innovation Agency (Innosuisse) flagship IICT (PFFS-21-47) and the German Ministry of Education and Research through the project So-cialWear (01IW20002).
Funders | Funder number |
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Microsoft AI | |
SignON | 101017255 |
Bundesministerium für Bildung und Forschung | 01IW20002 |
Horizon 2020 | 101016982 |
Innosuisse - Schweizerische Agentur für Innovationsförderung | PFFS-21-47 |
European Association for Machine Translation |