Spontaneous Catalan Sign Language Recognition: Data Acquisition and Classification

Naiara Garmendia; Horacio Saggion; Euan Mcgill

Spontaneous Catalan Sign Language Recognition: Data Acquisition and Classification

Naiara Garmendia, Horacio Saggion, Euan McGill

Correct Metadata for

Important: The Anthology treat PDFs as authoritative. Please use this form only to correct data that is out of line with the PDF. See our corrections guidelines if you need to change the PDF.

Title Adjust the title. Retain tags such as <fixed-case>.

Authors Adjust author names and order to match the PDF.

Abstract Correct abstract if needed. Retain XML formatting tags such as <tex-math>.

Verification against PDF Ensure that the new title/authors match the snapshot below. (If there is no snapshot or it is too small, consult the PDF.)

Authors concatenated from the text boxes above:

ALL author names match the snapshot above—including middle initials, hyphens, and accents.

Abstract

This work presents the first investigation into Spontaneous Isolated Sign Language Recognition for Catalan Sign Language (LSC). Our work is grounded on the derivation of a dataset of signs and their glosses from a corpus of spontaneous dialogues and monologues. The recognition model is based on a Multi-Scale Graph Convolutional network fitted to our data. Results are promising since several signs are recognized with a high level of accuracy, and an average accuracy of 71% on the top 5 predicted classes from a total of 105 available. An interactive interface with experimental results is also presented. The data and software are made available to the research community.

Anthology ID:: 2025.at4ssl-1.2
Volume:: Proceedings of the Third International Workshop on Automatic Translation for Signed and Spoken Languages (AT4SSL)
Month:: June
Year:: 2025
Address:: Geneva, Switzerland
Editors:: Dimitar Shterionov, Mirella De Sisto, Bram Vanroy, Vincent Vandeghinste, Victoria Nyst, Myriam Vermeerbergen, Floris Roelofsen, Lisa Lepp, Irene Strasly
Venue:: AT4SSL
SIG:
Publisher:: European Association for Machine Translation
Note:
Pages:: 7–15
Language:
URL:: https://aclanthology.org/2025.at4ssl-1.2/
DOI:
Bibkey:
Cite (ACL):: Naiara Garmendia, Horacio Saggion, and Euan McGill. 2025. Spontaneous Catalan Sign Language Recognition: Data Acquisition and Classification. In Proceedings of the Third International Workshop on Automatic Translation for Signed and Spoken Languages (AT4SSL), pages 7–15, Geneva, Switzerland. European Association for Machine Translation.
Cite (Informal):: Spontaneous Catalan Sign Language Recognition: Data Acquisition and Classification (Garmendia et al., AT4SSL 2025)
Copy Citation:
PDF:: https://aclanthology.org/2025.at4ssl-1.2.pdf

PDF Cite Search Fix data

Export citation

BibTeX
MODS XML
Endnote
Preformatted

@inproceedings{garmendia-etal-2025-spontaneous,
    title = "Spontaneous {C}atalan {S}ign {L}anguage Recognition: Data Acquisition and Classification",
    author = "Garmendia, Naiara  and
      Saggion, Horacio  and
      McGill, Euan",
    editor = "Shterionov, Dimitar  and
      Sisto, Mirella De  and
      Vanroy, Bram  and
      Vandeghinste, Vincent  and
      Nyst, Victoria  and
      Vermeerbergen, Myriam  and
      Roelofsen, Floris  and
      Lepp, Lisa  and
      Strasly, Irene",
    booktitle = "Proceedings of the Third International Workshop on Automatic Translation for Signed and Spoken Languages (AT4SSL)",
    month = jun,
    year = "2025",
    address = "Geneva, Switzerland",
    publisher = "European Association for Machine Translation",
    url = "https://aclanthology.org/2025.at4ssl-1.2/",
    pages = "7--15",
    ISBN = "978-2-9701897-3-2",
    abstract = "This work presents the first investigation into Spontaneous Isolated Sign Language Recognition for Catalan Sign Language (LSC). Our work is grounded on the derivation of a dataset of signs and their glosses from a corpus of spontaneous dialogues and monologues. The recognition model is based on a Multi-Scale Graph Convolutional network fitted to our data. Results are promising since several signs are recognized with a high level of accuracy, and an average accuracy of 71{\%} on the top 5 predicted classes from a total of 105 available. An interactive interface with experimental results is also presented. The data and software are made available to the research community."
}

Download as File

<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="garmendia-etal-2025-spontaneous">
    <titleInfo>
        <title>Spontaneous Catalan Sign Language Recognition: Data Acquisition and Classification</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Naiara</namePart>
        <namePart type="family">Garmendia</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Horacio</namePart>
        <namePart type="family">Saggion</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Euan</namePart>
        <namePart type="family">McGill</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2025-06</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Third International Workshop on Automatic Translation for Signed and Spoken Languages (AT4SSL)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Dimitar</namePart>
            <namePart type="family">Shterionov</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Mirella</namePart>
            <namePart type="given">De</namePart>
            <namePart type="family">Sisto</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Bram</namePart>
            <namePart type="family">Vanroy</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Vincent</namePart>
            <namePart type="family">Vandeghinste</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Victoria</namePart>
            <namePart type="family">Nyst</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Myriam</namePart>
            <namePart type="family">Vermeerbergen</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Floris</namePart>
            <namePart type="family">Roelofsen</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Lisa</namePart>
            <namePart type="family">Lepp</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Irene</namePart>
            <namePart type="family">Strasly</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>European Association for Machine Translation</publisher>
            <place>
                <placeTerm type="text">Geneva, Switzerland</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
        <identifier type="isbn">978-2-9701897-3-2</identifier>
    </relatedItem>
    <abstract>This work presents the first investigation into Spontaneous Isolated Sign Language Recognition for Catalan Sign Language (LSC). Our work is grounded on the derivation of a dataset of signs and their glosses from a corpus of spontaneous dialogues and monologues. The recognition model is based on a Multi-Scale Graph Convolutional network fitted to our data. Results are promising since several signs are recognized with a high level of accuracy, and an average accuracy of 71% on the top 5 predicted classes from a total of 105 available. An interactive interface with experimental results is also presented. The data and software are made available to the research community.</abstract>
    <identifier type="citekey">garmendia-etal-2025-spontaneous</identifier>
    <location>
        <url>https://aclanthology.org/2025.at4ssl-1.2/</url>
    </location>
    <part>
        <date>2025-06</date>
        <extent unit="page">
            <start>7</start>
            <end>15</end>
        </extent>
    </part>
</mods>
</modsCollection>

Download as File

%0 Conference Proceedings
%T Spontaneous Catalan Sign Language Recognition: Data Acquisition and Classification
%A Garmendia, Naiara
%A Saggion, Horacio
%A McGill, Euan
%Y Shterionov, Dimitar
%Y Sisto, Mirella De
%Y Vanroy, Bram
%Y Vandeghinste, Vincent
%Y Nyst, Victoria
%Y Vermeerbergen, Myriam
%Y Roelofsen, Floris
%Y Lepp, Lisa
%Y Strasly, Irene
%S Proceedings of the Third International Workshop on Automatic Translation for Signed and Spoken Languages (AT4SSL)
%D 2025
%8 June
%I European Association for Machine Translation
%C Geneva, Switzerland
%@ 978-2-9701897-3-2
%F garmendia-etal-2025-spontaneous
%X This work presents the first investigation into Spontaneous Isolated Sign Language Recognition for Catalan Sign Language (LSC). Our work is grounded on the derivation of a dataset of signs and their glosses from a corpus of spontaneous dialogues and monologues. The recognition model is based on a Multi-Scale Graph Convolutional network fitted to our data. Results are promising since several signs are recognized with a high level of accuracy, and an average accuracy of 71% on the top 5 predicted classes from a total of 105 available. An interactive interface with experimental results is also presented. The data and software are made available to the research community.
%U https://aclanthology.org/2025.at4ssl-1.2/
%P 7-15

Download as File

Markdown (Informal)

[Spontaneous Catalan Sign Language Recognition: Data Acquisition and Classification](https://aclanthology.org/2025.at4ssl-1.2/) (Garmendia et al., AT4SSL 2025)

Spontaneous Catalan Sign Language Recognition: Data Acquisition and Classification (Garmendia et al., AT4SSL 2025)

ACL

Naiara Garmendia, Horacio Saggion, and Euan McGill. 2025. Spontaneous Catalan Sign Language Recognition: Data Acquisition and Classification. In Proceedings of the Third International Workshop on Automatic Translation for Signed and Spoken Languages (AT4SSL), pages 7–15, Geneva, Switzerland. European Association for Machine Translation.