Smart ISL Recognition & Translation System A Survey

Productive communication between people with speech and hearing disabilities and the general public continues to be a pressing challenge. This paper presents a survey for two-way, real-time communication systems aimed at identifying and interpreting Indian Sign Language into text and speech and speech to text. The system, through the use of a mix of computer-vision, natural- language-processing, machine-learning, and speech- processing-technologies, translates hand gestures through Natural-Language-Processing (NLP), MediaPipe and OpenCV for gesture-to-text/speech to regional language conversion and text-to-sign conversion. On the other hand, it converts text language into animated sign representations, which increase the accessibility of deaf users and subsequently when video or image is used as input it outputs corresponding text increasing communication between normal and special users. Real-time performance, high accuracy, and scalability are prioritized on the platform with affordability guaranteed via open-source tools.

Authors

Publication Details

Journal
Technix International Journal for Engineering Research
Published
2025-01-01
DOI
https://doi.org/10.56975/tijer.v12i7.159310
Primary Topic
Machine Learning in Bioinformatics
Type
article
Field-Weighted Citation Impact
0.00
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article

Smart ISL Recognition & Translation System A Survey

G. A. Dhanush, Nandita Bangera, Antonio R. Jiménez, J. Prakash et al.
Technix International Journal for Engineering Research
Machine Learning in Bioinformatics
article

Smart ISL Recognition & Translation System A Survey

G. A. Dhanush, Nandita Bangera, Antonio R. Jiménez, J. Prakash, D Gagandeep
article en

Abstract

Productive communication between people with speech and hearing disabilities and the general public continues to be a pressing challenge. This paper presents a survey for two-way, real-time communication systems aimed at identifying and interpreting Indian Sign Language into text and speech and speech to text. The system, through the use of a mix of computer-vision, natural- language-processing, machine-learning, and speech- processing-technologies, translates hand gestures through Natural-Language-Processing (NLP), MediaPipe and OpenCV for gesture-to-text/speech to regional language conversion and text-to-sign conversion. On the other hand, it converts text language into animated sign representations, which increase the accessibility of deaf users and subsequently when video or image is used as input it outputs corresponding text increasing communication between normal and special users. Real-time performance, high accuracy, and scalability are prioritized on the platform with affordability guaranteed via open-source tools.

Technix International Journal for Engineering ResearchVol. 12(7)
Openalex Percentile: Top 83%
Machine Learning in Bioinformatics
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Smart ISL Recognition & Translation System A Survey — G. A. Dhanush, Nandita Bangera, et al. · Technix International Journal for Engineering Research (2025) | TGRS Research Map | TGRS