<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="sousa-etal-2023-enhancing">
    <titleInfo>
        <title>Enhancing Accessible Communication: from European Portuguese to Portuguese Sign Language</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Catarina</namePart>
        <namePart type="family">Sousa</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Luisa</namePart>
        <namePart type="family">Coheur</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Mara</namePart>
        <namePart type="family">Moita</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2023-12</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Findings of the Association for Computational Linguistics: EMNLP 2023</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Houda</namePart>
            <namePart type="family">Bouamor</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Juan</namePart>
            <namePart type="family">Pino</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Kalika</namePart>
            <namePart type="family">Bali</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Singapore</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <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.</abstract>
    <identifier type="citekey">sousa-etal-2023-enhancing</identifier>
    <identifier type="doi">10.18653/v1/2023.findings-emnlp.766</identifier>
    <location>
        <url>https://aclanthology.org/2023.findings-emnlp.766</url>
    </location>
    <part>
        <date>2023-12</date>
        <extent unit="page">
            <start>11452</start>
            <end>11460</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Enhancing Accessible Communication: from European Portuguese to Portuguese Sign Language
%A Sousa, Catarina
%A Coheur, Luisa
%A Moita, Mara
%Y Bouamor, Houda
%Y Pino, Juan
%Y Bali, Kalika
%S Findings of the Association for Computational Linguistics: EMNLP 2023
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F sousa-etal-2023-enhancing
%X 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.
%R 10.18653/v1/2023.findings-emnlp.766
%U https://aclanthology.org/2023.findings-emnlp.766
%U https://doi.org/10.18653/v1/2023.findings-emnlp.766
%P 11452-11460

Markdown (Informal)

[Enhancing Accessible Communication: from European Portuguese to Portuguese Sign Language](https://aclanthology.org/2023.findings-emnlp.766) (Sousa et al., Findings 2023)

• Enhancing Accessible Communication: from European Portuguese to Portuguese Sign Language (Sousa et al., Findings 2023)

ACL

• Catarina Sousa, Luisa Coheur, and Mara Moita. 2023. Enhancing Accessible Communication: from European Portuguese to Portuguese Sign Language. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 11452–11460, Singapore. Association for Computational Linguistics.