ISL(Indian Sign Language) Gesture to Speech with Multilingual Support

The Real Time Indian Sign Language (ISL) Translator project aims to bridge the communication gap between the deaf and hard of hearing community and the hearing world by leveraging advanced deep learning techniques. This project utilizes Convolutional Neural Networks (CNNs) to recognize the ISL gesture and converts them into text. The recognized text is then translated into speech in multiple Indian languages, allowing seamless real time communication. The system is comprised of three primary components: the Gesture Recognition Module, which employs a CNN to process real time video input of ISL gestures; the Text processing Module, which converts the recognized gesture into structured text; and the Text to Speech (TTS) Module, which translates the test into speech in various Indian languages. An additional Language Selection Module provides users with the option to choose their preferred language for the TTS output. To ensure accessibility and usability, this project integrates a user friendly website interface, enabling individuals to use the translator easily across different platform. By fostering greater inclusion and improving communication in social, educational, and professional settings, the Real Time ISL Translator project stands as a significant technological advancement for the deaf and hard of hearing community in India.

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Publication Details

Published
2024-11-23
DOI
https://doi.org/10.59544/lnzk4758/icrcct24p70
Primary Topic
Hearing Impairment and Communication
Type
article
Field-Weighted Citation Impact
0.00
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article

ISL(Indian Sign Language) Gesture to Speech with Multilingual Support

G. Fathima, M Mukunda, Sasi Kumar, Ms. Vijayalakshmi S et al.
Hearing Impairment and Communication
article

ISL(Indian Sign Language) Gesture to Speech with Multilingual Support

G. Fathima, M Mukunda, Sasi Kumar, Ms. Vijayalakshmi S, SIVA SUBRAMANIAN E -
article en

Abstract

The Real Time Indian Sign Language (ISL) Translator project aims to bridge the communication gap between the deaf and hard of hearing community and the hearing world by leveraging advanced deep learning techniques. This project utilizes Convolutional Neural Networks (CNNs) to recognize the ISL gesture and converts them into text. The recognized text is then translated into speech in multiple Indian languages, allowing seamless real time communication. The system is comprised of three primary components: the Gesture Recognition Module, which employs a CNN to process real time video input of ISL gestures; the Text processing Module, which converts the recognized gesture into structured text; and the Text to Speech (TTS) Module, which translates the test into speech in various Indian languages. An additional Language Selection Module provides users with the option to choose their preferred language for the TTS output. To ensure accessibility and usability, this project integrates a user friendly website interface, enabling individuals to use the translator easily across different platform. By fostering greater inclusion and improving communication in social, educational, and professional settings, the Real Time ISL Translator project stands as a significant technological advancement for the deaf and hard of hearing community in India.

Reduced inequalities
Openalex Percentile: Top 74%
Hearing Impairment and Communication
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