Authors :
Gaddala Finny Theophorus; Balwant Singh
Volume/Issue :
Volume 9 - 2024, Issue 5 - May
Google Scholar :
https://tinyurl.com/y7yj5rbx
Scribd :
https://tinyurl.com/mt8mrekd
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24MAY2510
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
" Intersign Glove " is a groundbreaking
innovation designed to address the communication
barriers faced by the deaf and mute community. With the
aim of revolutionizing traditional methods of
communication, this paper introduces an innovative
approach that utilizes gesture recognition technology to
interpret Indian Sign Language (ISL) in real-time. The
paper endeavors to eliminate the dependency on sign
language interpreters by creating an embedded system
comprising both hardware and software components. By
leveraging advanced sensors strategically placed on a
glove, the system captures intricate gesture parameters
and translates them into code for computation. This code
is then processed by a microcontroller board integrated
into the glove, which generates corresponding speech
output through an attached speaker, facilitating seamless
communication between the user and non-sign language
speakers. The wearable nature of the device ensures
portability and ease of use, empowering individuals with
hearing and speech impairments to communicate
effectively in various social settings. Furthermore, by
bridging the communication gap between the deaf and
mute community and the wider population, this paper
opens up new opportunities for inclusion and
collaboration. "Intersign Glove" represents a significant
advancement in assistive technology, promising to enhance
the quality of life for individuals with hearing and speech
disabilities while fostering greater understanding and
integration within society.
Keywords :
Intersign Glove, Sign Language.
References :
[1]. Vasani, N., Autee, P., Kalyani, S., &Karani, R. (2020). Generation of Indian sign language by sentence processing and generative adversarial networks. Proceedings of the Third International Conference on Intelligent Sustainable Systems [ICISS 2020], 1250-1255. https://doi.org/10.1109/ICISS49785.2020. 9315979
[2]. Kahlon, N. K., &Singh, W. (2021). Machine translation from text to sign language: a systematic review. Universal Access in the Information Society, 1-36. https://doi.org/10.1007/s10209-021-00823-1
[3]. B. G. Lee and S. M. Lee, "Smart Wearable Hand Device for Sign Language Interpretation System With Sensors Fusion," in IEEE Sensors Journal, vol. 18, no. 3, pp. 1224-1232, 1 Feb.1, 2018, doi: 10.1109/JSEN.2017.2779466.
[4]. Sampada.S. Wazalwar & Urmila Shrawankar (2017) Interpretation of sign language into English using NLP techniques, Journal of Information and Optimization Sciences, 38:6, 895-910, DOI: 10.1080/02522667. 2017.1372136
[5]. T. Yuan et al., "Large Scale Sign Language Interpretation," 2019 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019), Lille, France, 2019, pp. 1-5, doi: 10.1109/FG.2019.8756506.
[6]. Paul, P., Bhuiya, M.AUA., Ullah, M.A., Saqib, M.N., Mohammed, N., Momen, S. (2019). A Modern Approach for Sign Language Interpretation Using Convolutional Neural Network. In: Nayak, A., Sharma, A. (eds) PRICAI 2019: Trends in Artificial Intelligence. PRICAI 2019. Lecture Notes in Computer Science(), vol 11672. Springer, Cham. https://doi.org/10.1007/978-3-030-29894-4_35
[7]. Lee, B.G., Chung, W.Y. (2021). Study of Sign Language Recognition Using Wearable Sensors. In: Singh, M., Kang, DK., Lee, JH., Tiwary, U.S., Singh, D., Chung, WY. (eds) Intelligent Human Computer Interaction. IHCI 2020. Lecture Notes in Computer Science(), vol 12615. Springer, Cham. https://doi.org/10.1007/978-3-030-68449-5_24
[8]. Golda Jeyasheeli P and Annapoorani K Miss 2019 J. Phys.: Conf. Ser. 1362 012034DOI 10.1088/1742-6596/1362/1/012034
" Intersign Glove " is a groundbreaking
innovation designed to address the communication
barriers faced by the deaf and mute community. With the
aim of revolutionizing traditional methods of
communication, this paper introduces an innovative
approach that utilizes gesture recognition technology to
interpret Indian Sign Language (ISL) in real-time. The
paper endeavors to eliminate the dependency on sign
language interpreters by creating an embedded system
comprising both hardware and software components. By
leveraging advanced sensors strategically placed on a
glove, the system captures intricate gesture parameters
and translates them into code for computation. This code
is then processed by a microcontroller board integrated
into the glove, which generates corresponding speech
output through an attached speaker, facilitating seamless
communication between the user and non-sign language
speakers. The wearable nature of the device ensures
portability and ease of use, empowering individuals with
hearing and speech impairments to communicate
effectively in various social settings. Furthermore, by
bridging the communication gap between the deaf and
mute community and the wider population, this paper
opens up new opportunities for inclusion and
collaboration. "Intersign Glove" represents a significant
advancement in assistive technology, promising to enhance
the quality of life for individuals with hearing and speech
disabilities while fostering greater understanding and
integration within society.