A Review on Multilingual Sign Language Translator
- DOI
- 10.2991/978-94-6463-858-5_266How to use a DOI?
- Keywords
- Sign language translation; deep learning; multilingual sign language; contactless recognition; graph neural networks; accessibility; text-based intermediate translation; real time application
- Abstract
Sign language translation systems have been studied over and over and have become really important for helping deaf people talk to those who hear every day. This paper is a broad overview of what recent critical progress has been made in the conversion of one sign language into another, conveying efforts to create seamless translation that improved people’s communication with each other using the intermediate medium of text. Various deep learning models, including CNNs, RNNs, and GANs, have been evaluated through different techniques for sign language recognition and translation Techniques for sensor-based recognition, contactless recognition systems, and graph based feature extraction are used to describe what is currently possible.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Durgam Deekshita AU - Panumati Shravani AU - Wendy Marla R. Marak AU - S. M. Naveen Raja PY - 2025 DA - 2025/11/04 TI - A Review on Multilingual Sign Language Translator BT - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025) PB - Atlantis Press SP - 3194 EP - 3206 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-858-5_266 DO - 10.2991/978-94-6463-858-5_266 ID - Deekshita2025 ER -