Year: 2024
Type: article
Abstract: This work focuses on the creation of tools to help deaf people learn Arabic Algerian Sign Language (ALSL), specifically an automatic translation system with a 3D avatar for accurate and dynamic sign representation. The system encodes ALSL signs using the Notation System Method (NSM), which is principally based on the Hamburg Notation System (HamNoSys). A shallow analysis of the linguistic complexity of ALSL is offered, as well as the obstacles inherent in developing technological solutions to facilitate proper translation. To ensure correctness, the development approach involved working with ALSL translation experts at each level. The system's lexicon, consisting of 417 words, achieved a certified accuracy rate of 75.53%. These results represent a substantial step forward in 3D avatar-based sign language simulation, with opportunities for further refinement and development.
DOI: 10.54455/mcn2804
Authors: Amine Mami, Mohamed Elfares Slimani, Taha Zerrouki, Redha Mazari
Institutions: University Yahia Fares of Medea, University of Bouira
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4407602931