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DOI: 10.14569/IJACSA.2024.01504114
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Harnessing AI to Generate Indian Sign Language from Natural Speech and Text for Digital Inclusion and Accessibility

Author 1: Parul Yadav
Author 2: Puneet Sharma
Author 3: Pooja Khanna
Author 4: Mahima Chawla
Author 5: Rishi Jain
Author 6: Laiba Noor

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 4, 2024.

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Abstract: Sign language is the fundamental mode of communication for those who are deaf and mute, as well as for individuals with hearing impairments. Regrettably, there has been a dearth of research on Indian Sign Language, primarily due to the lack of adequate grammar and regional variations in such language. Consequently, research in this area has been limited. The primary objective of our research is to develop a sophisticated speech/ text-to-Indian sign language conversion system that employs advanced 3D modeling techniques to display sign language motions. Our research is motivated by our desire to promote effective communication between hearing and hearing-impaired individuals in India. The proposed model integrates Automatic Speech Recognition (ASR) technology, which effectively transforms spoken words into text, and leverages 3D modeling techniques to generate corresponding sign language motions. We have conducted a comprehensive study of the grammar of Indian Sign Language, which includes identifying sentence structure and signs that represent the tense of the subject. It is noteworthy that the sentence structure of Indian Sign Language follows the Subject-Object-Verb sequence, in contrast to spoken language, which follows the Subject-Verb-Object structure. To enhance user experience as well as digital inclusion and accessibility, the research incorporates user-friendly and simple interfaces that allow individuals to interact effortlessly with the system intuitively. The model/ system is equipped to receive speech input through a microphone/ text and provide immediate feedback through 3D-modeled videos that display the generated sign language gestures and has achieved 99.2% accuracy. Our main goal is to promote digital inclusion and improve accessibility and enhance the user experience.

Keywords: Sign language generation; automatic speech recognition; speech-to-indian sign language; indian sign language; digital inclusion and accessibility

Parul Yadav, Puneet Sharma, Pooja Khanna, Mahima Chawla, Rishi Jain and Laiba Noor, “Harnessing AI to Generate Indian Sign Language from Natural Speech and Text for Digital Inclusion and Accessibility” International Journal of Advanced Computer Science and Applications(IJACSA), 15(4), 2024. http://dx.doi.org/10.14569/IJACSA.2024.01504114

@article{Yadav2024,
title = {Harnessing AI to Generate Indian Sign Language from Natural Speech and Text for Digital Inclusion and Accessibility},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.01504114},
url = {http://dx.doi.org/10.14569/IJACSA.2024.01504114},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {4},
author = {Parul Yadav and Puneet Sharma and Pooja Khanna and Mahima Chawla and Rishi Jain and Laiba Noor}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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