@inproceedings{imashev-etal-2024-comparative-analysis,
title = "Comparative Analysis of Sign Language Interpreting Agents Perception: A Study of the Deaf",
author = "Imashev, Alfarabi and
Oralbayeva, Nurziya and
Baizhanova, Gulmira and
Sandygulova, Anara",
editor = "Calzolari, Nicoletta and
Kan, Min-Yen and
Hoste, Veronique and
Lenci, Alessandro and
Sakti, Sakriani and
Xue, Nianwen",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.lrec-main.319",
pages = "3603--3609",
abstract = "Prior research on sign language recognition has already demonstrated encouraging outcomes in achieving highly accurate and dependable automatic sign language recognition. The use of virtual characters as virtual assistants has significantly increased in the past decade. However, the progress in sign language generation and output that closely resembles physiologically believable human motions is still in its early stages. This assertion explains the lack of progress in virtual intelligent signing generative systems. Aside from the development of signing systems, scholarly research have revealed a significant deficiency in evaluating sign language generation systems by those who are deaf and use sign language. This paper presents the findings of a user study conducted with deaf signers. The study is aimed at comparing a state-of-the-art sign language generation system with a skilled sign language interpreter. The study focused on testing established metrics to gain insights into usability of such metrics for deaf signers and how deaf signers perceive signing agents.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="imashev-etal-2024-comparative-analysis">
<titleInfo>
<title>Comparative Analysis of Sign Language Interpreting Agents Perception: A Study of the Deaf</title>
</titleInfo>
<name type="personal">
<namePart type="given">Alfarabi</namePart>
<namePart type="family">Imashev</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Nurziya</namePart>
<namePart type="family">Oralbayeva</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Gulmira</namePart>
<namePart type="family">Baizhanova</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Anara</namePart>
<namePart type="family">Sandygulova</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2024-05</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Nicoletta</namePart>
<namePart type="family">Calzolari</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Min-Yen</namePart>
<namePart type="family">Kan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Veronique</namePart>
<namePart type="family">Hoste</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alessandro</namePart>
<namePart type="family">Lenci</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Sakriani</namePart>
<namePart type="family">Sakti</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Nianwen</namePart>
<namePart type="family">Xue</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>ELRA and ICCL</publisher>
<place>
<placeTerm type="text">Torino, Italia</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Prior research on sign language recognition has already demonstrated encouraging outcomes in achieving highly accurate and dependable automatic sign language recognition. The use of virtual characters as virtual assistants has significantly increased in the past decade. However, the progress in sign language generation and output that closely resembles physiologically believable human motions is still in its early stages. This assertion explains the lack of progress in virtual intelligent signing generative systems. Aside from the development of signing systems, scholarly research have revealed a significant deficiency in evaluating sign language generation systems by those who are deaf and use sign language. This paper presents the findings of a user study conducted with deaf signers. The study is aimed at comparing a state-of-the-art sign language generation system with a skilled sign language interpreter. The study focused on testing established metrics to gain insights into usability of such metrics for deaf signers and how deaf signers perceive signing agents.</abstract>
<identifier type="citekey">imashev-etal-2024-comparative-analysis</identifier>
<location>
<url>https://aclanthology.org/2024.lrec-main.319</url>
</location>
<part>
<date>2024-05</date>
<extent unit="page">
<start>3603</start>
<end>3609</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Comparative Analysis of Sign Language Interpreting Agents Perception: A Study of the Deaf
%A Imashev, Alfarabi
%A Oralbayeva, Nurziya
%A Baizhanova, Gulmira
%A Sandygulova, Anara
%Y Calzolari, Nicoletta
%Y Kan, Min-Yen
%Y Hoste, Veronique
%Y Lenci, Alessandro
%Y Sakti, Sakriani
%Y Xue, Nianwen
%S Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F imashev-etal-2024-comparative-analysis
%X Prior research on sign language recognition has already demonstrated encouraging outcomes in achieving highly accurate and dependable automatic sign language recognition. The use of virtual characters as virtual assistants has significantly increased in the past decade. However, the progress in sign language generation and output that closely resembles physiologically believable human motions is still in its early stages. This assertion explains the lack of progress in virtual intelligent signing generative systems. Aside from the development of signing systems, scholarly research have revealed a significant deficiency in evaluating sign language generation systems by those who are deaf and use sign language. This paper presents the findings of a user study conducted with deaf signers. The study is aimed at comparing a state-of-the-art sign language generation system with a skilled sign language interpreter. The study focused on testing established metrics to gain insights into usability of such metrics for deaf signers and how deaf signers perceive signing agents.
%U https://aclanthology.org/2024.lrec-main.319
%P 3603-3609
Markdown (Informal)
[Comparative Analysis of Sign Language Interpreting Agents Perception: A Study of the Deaf](https://aclanthology.org/2024.lrec-main.319) (Imashev et al., LREC-COLING 2024)
ACL