Enhancing accessible communication: from European Portuguese to Portuguese Sign Language

Catarina Sousa; Luísa Coheur; Mara Moita

doi:10.18653/v1/2023.findings-emnlp.766

Enhancing accessible communication: from European Portuguese to Portuguese Sign Language

Catarina Sousa, Luísa Coheur, Mara Moita

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Abstract

Portuguese Sign Language (LGP) is the official language in deaf education in Portugal. Current approaches in developing a translation system between European Portuguese and LGP rely on hand-crafted rules. In this paper, we present a fully automatic corpora-driven rule-based machine translation system between European Portuguese and LGP glosses, and also two neural machine translation models. We also contribute with the LGP-5-Domain corpus, composed of five different text domains, built with the help of our rule-based system, and used to train the neural models. In addition, we provide a gold collection, annotated by LGP experts, that can be used for future evaluations. Compared with the only similar available translation system, PE2LGP, results are always improved with the new rule-based model, which competes for the highest scores with one of the neural models.

Original language	English
Title of host publication	Findings of the Association for Computational Linguistics
Subtitle of host publication	EMNLP 2023
Publisher	Association for Computational Linguistics (ACL)
Pages	11452-11460
Number of pages	9
ISBN (Electronic)	9798891760615
ISBN (Print)	9781959429470
DOIs	https://doi.org/10.18653/v1/2023.findings-emnlp.766
Publication status	Published - 2023
Event	2023 Findings of the Association for Computational Linguistics: EMNLP 2023 - Resorts World Convention Centre, Singapore, Singapore Duration: 6 Dec 2023 → 10 Dec 2023

Conference

Conference	2023 Findings of the Association for Computational Linguistics
Country/Territory	Singapore
City	Singapore
Period	6/12/23 → 10/12/23

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10.18653/v1/2023.findings-emnlp.766Licence: CC BY

93084643Final published version, 286 KBLicence: CC BY

http://hdl.handle.net/10400.14/43860Licence: CC BY

Cite this

@inproceedings{1e82e01541924c38b178e0ade059089f,

title = "Enhancing accessible communication: from European Portuguese to Portuguese Sign Language",

abstract = "Portuguese Sign Language (LGP) is the official language in deaf education in Portugal. Current approaches in developing a translation system between European Portuguese and LGP rely on hand-crafted rules. In this paper, we present a fully automatic corpora-driven rule-based machine translation system between European Portuguese and LGP glosses, and also two neural machine translation models. We also contribute with the LGP-5-Domain corpus, composed of five different text domains, built with the help of our rule-based system, and used to train the neural models. In addition, we provide a gold collection, annotated by LGP experts, that can be used for future evaluations. Compared with the only similar available translation system, PE2LGP, results are always improved with the new rule-based model, which competes for the highest scores with one of the neural models.",

author = "Catarina Sousa and Lu{\'i}sa Coheur and Mara Moita",

note = "Publisher Copyright: {\textcopyright} 2023 Association for Computational Linguistics.; 2023 Findings of the Association for Computational Linguistics : EMNLP 2023 ; Conference date: 06-12-2023 Through 10-12-2023",

year = "2023",

doi = "10.18653/v1/2023.findings-emnlp.766",

language = "English",

isbn = "9781959429470",

pages = "11452--11460",

booktitle = "Findings of the Association for Computational Linguistics",

publisher = "Association for Computational Linguistics (ACL)",

address = "United States",

}

Sousa, C, Coheur, L & Moita, M 2023, Enhancing accessible communication: from European Portuguese to Portuguese Sign Language. in Findings of the Association for Computational Linguistics: EMNLP 2023. Association for Computational Linguistics (ACL), pp. 11452-11460, 2023 Findings of the Association for Computational Linguistics, Singapore, Singapore, 6/12/23. https://doi.org/10.18653/v1/2023.findings-emnlp.766

Enhancing accessible communication: from European Portuguese to Portuguese Sign Language. / Sousa, Catarina; Coheur, Luísa; Moita, Mara.
Findings of the Association for Computational Linguistics: EMNLP 2023. Association for Computational Linguistics (ACL), 2023. p. 11452-11460.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Portuguese Sign Language (LGP) is the official language in deaf education in Portugal. Current approaches in developing a translation system between European Portuguese and LGP rely on hand-crafted rules. In this paper, we present a fully automatic corpora-driven rule-based machine translation system between European Portuguese and LGP glosses, and also two neural machine translation models. We also contribute with the LGP-5-Domain corpus, composed of five different text domains, built with the help of our rule-based system, and used to train the neural models. In addition, we provide a gold collection, annotated by LGP experts, that can be used for future evaluations. Compared with the only similar available translation system, PE2LGP, results are always improved with the new rule-based model, which competes for the highest scores with one of the neural models.

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Enhancing accessible communication: from European Portuguese to Portuguese Sign Language

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CIIS: Center for Interdisciplinary Research in Health

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Enhancing accessible communication: from European Portuguese to Portuguese Sign Language

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CIIS: Center for Interdisciplinary Research in Health

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