Translating Spanish into Spanish Sign Language: Combining Rules and Data-driven Approaches

Luis Chiruzzo; Euan Mcgill; Santiago Egea-Gómez; Horacio Saggion

Translating Spanish into Spanish Sign Language: Combining Rules and Data-driven Approaches

Luis Chiruzzo, Euan McGill, Santiago Egea-Gómez, Horacio Saggion

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Abstract

This paper presents a series of experiments on translating between spoken Spanish and Spanish Sign Language glosses (LSE), including enriching Neural Machine Translation (NMT) systems with linguistic features, and creating synthetic data to pretrain and later on finetune a neural translation model. We found evidence that pretraining over a large corpus of LSE synthetic data aligned to Spanish sentences could markedly improve the performance of the translation models.

Anthology ID:: 2022.loresmt-1.10
Volume:: Proceedings of the Fifth Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2022)
Month:: October
Year:: 2022
Address:: Gyeongju, Republic of Korea
Editors:: Atul Kr. Ojha, Chao-Hong Liu, Ekaterina Vylomova, Jade Abbott, Jonathan Washington, Nathaniel Oco, Tommi A Pirinen, Valentin Malykh, Varvara Logacheva, Xiaobing Zhao
Venue:: LoResMT
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 75–83
Language:
URL:: https://aclanthology.org/2022.loresmt-1.10/
DOI:
Bibkey:
Cite (ACL):: Luis Chiruzzo, Euan McGill, Santiago Egea-Gómez, and Horacio Saggion. 2022. Translating Spanish into Spanish Sign Language: Combining Rules and Data-driven Approaches. In Proceedings of the Fifth Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2022), pages 75–83, Gyeongju, Republic of Korea. Association for Computational Linguistics.
Cite (Informal):: Translating Spanish into Spanish Sign Language: Combining Rules and Data-driven Approaches (Chiruzzo et al., LoResMT 2022)
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PDF:: https://aclanthology.org/2022.loresmt-1.10.pdf

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@inproceedings{chiruzzo-etal-2022-translating,
    title = "Translating {S}panish into {S}panish {S}ign {L}anguage: Combining Rules and Data-driven Approaches",
    author = "Chiruzzo, Luis  and
      McGill, Euan  and
      Egea-G{\'o}mez, Santiago  and
      Saggion, Horacio",
    editor = "Ojha, Atul Kr.  and
      Liu, Chao-Hong  and
      Vylomova, Ekaterina  and
      Abbott, Jade  and
      Washington, Jonathan  and
      Oco, Nathaniel  and
      Pirinen, Tommi A  and
      Malykh, Valentin  and
      Logacheva, Varvara  and
      Zhao, Xiaobing",
    booktitle = "Proceedings of the Fifth Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2022)",
    month = oct,
    year = "2022",
    address = "Gyeongju, Republic of Korea",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.loresmt-1.10/",
    pages = "75--83",
    abstract = "This paper presents a series of experiments on translating between spoken Spanish and Spanish Sign Language glosses (LSE), including enriching Neural Machine Translation (NMT) systems with linguistic features, and creating synthetic data to pretrain and later on finetune a neural translation model. We found evidence that pretraining over a large corpus of LSE synthetic data aligned to Spanish sentences could markedly improve the performance of the translation models."
}

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%0 Conference Proceedings
%T Translating Spanish into Spanish Sign Language: Combining Rules and Data-driven Approaches
%A Chiruzzo, Luis
%A McGill, Euan
%A Egea-Gómez, Santiago
%A Saggion, Horacio
%Y Ojha, Atul Kr.
%Y Liu, Chao-Hong
%Y Vylomova, Ekaterina
%Y Abbott, Jade
%Y Washington, Jonathan
%Y Oco, Nathaniel
%Y Pirinen, Tommi A.
%Y Malykh, Valentin
%Y Logacheva, Varvara
%Y Zhao, Xiaobing
%S Proceedings of the Fifth Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2022)
%D 2022
%8 October
%I Association for Computational Linguistics
%C Gyeongju, Republic of Korea
%F chiruzzo-etal-2022-translating
%X This paper presents a series of experiments on translating between spoken Spanish and Spanish Sign Language glosses (LSE), including enriching Neural Machine Translation (NMT) systems with linguistic features, and creating synthetic data to pretrain and later on finetune a neural translation model. We found evidence that pretraining over a large corpus of LSE synthetic data aligned to Spanish sentences could markedly improve the performance of the translation models.
%U https://aclanthology.org/2022.loresmt-1.10/
%P 75-83

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Markdown (Informal)

[Translating Spanish into Spanish Sign Language: Combining Rules and Data-driven Approaches](https://aclanthology.org/2022.loresmt-1.10/) (Chiruzzo et al., LoResMT 2022)

Translating Spanish into Spanish Sign Language: Combining Rules and Data-driven Approaches (Chiruzzo et al., LoResMT 2022)

ACL

Luis Chiruzzo, Euan McGill, Santiago Egea-Gómez, and Horacio Saggion. 2022. Translating Spanish into Spanish Sign Language: Combining Rules and Data-driven Approaches. In Proceedings of the Fifth Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2022), pages 75–83, Gyeongju, Republic of Korea. Association for Computational Linguistics.