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Automated Sign Language Vocabulary Assessment: Comparing Human and Machine Ratings and Studying Learner Perceptions

Holzknecht, Franz; Tornay, Sandrine; Battisti, Alessia; Batty, Aaron Olaf; Tissi, Katja; Haug, Tobias; Ebling, Sarah (2024). Automated Sign Language Vocabulary Assessment: Comparing Human and Machine Ratings and Studying Learner Perceptions. Language Assessment Quarterly, 21(3):245-265.

Abstract

Although automated spoken language assessment is rapidly growing, such systems have not been widely developed for signed languages. This study provides validity evidence for an automated web application that was developed to assess and give feedback on handshape and hand movement of L2 learners’ Swiss German Sign Language signs. The study shows good machine-internal and human-machine agreement through many-facet Rasch analysis. Learner perceptions examined through questionnaire responses indicate that the automated system occasionally generated ratings which impacted the quality of feedback at the level of individual signs for individual learners. Implications are discussed from a learning-oriented assessment perspective.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:410 Linguistics
000 Computer science, knowledge & systems
Scopus Subject Areas:Social Sciences & Humanities > Language and Linguistics
Social Sciences & Humanities > Linguistics and Language
Language:English
Date:26 May 2024
Deposited On:04 Dec 2024 14:25
Last Modified:09 Dec 2024 12:11
Publisher:Routledge
ISSN:1543-4303
OA Status:Hybrid
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1080/15434303.2024.2364877
Project Information:
  • Funder: SNSF
  • Grant ID: 193686
  • Project Title: SMILE-II
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  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)

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