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International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
Collaboration across disciplines will be vital in realizing [4] Real-Time Translation Devices for Sign Language by L.
these goals. By prioritizing innovation and inclusivity, Chen et al. (2021): [invalid URL removed]
researchers can help create a world where communication [5] Legal Recognition of Sign Languages: A Global
barriers for the deaf community no longer exist.
Overview by T. Johnson (2018): [invalid URL
Ø 1960s: William Stokoe's research on ASL structure lays removed]
the groundwork for future technological advancements.
[6] AI-Based Sign Language Recognition Systems by X. Li
Ø 1970s: Early attempts at automated sign recognition and H. Wang (2020):
using gloves and sensors. https://www.frontiersin.org/journals/artificial-
intelligence/articles/10.3389/frai.2024.1297347/pdf
Ø 1980s: Development of computer vision techniques for
hand tracking and gesture recognition. [7] Education and Bilingual Programs for the Deaf by C.
Brown (2022): [invalid URL removed]
Ø 1990s: First prototypes of sign language recognition
systems using hidden Markov models. [8] Virtual Reality in Sign Language Education by M.
Garcia (2019): https://www.mdpi.com/2227-
Ø 2000s: Machine learning algorithms, such as Support 7080/11/4/83
Vector Machines (SVMs), improve sign recognition
accuracy. [9] Challenges in Developing Low-Cost Assistive Devices
by A. Singh (2020):
Ø 2010s: Deep learning revolutionizes sign language https://www.ncbi.nlm.nih.gov/pmc/articles/PMC811
recognition with the use of Convolutional Neural 3838/
Networks (CNNs) and Recurrent Neural Networks
(RNNs). [10] Comparative Studies in Regional Sign Languages by R.
Davis (2021):
Ø Present: Advancements in computer vision, natural https://www.frontiersin.org/journals/artificial-
language processing, and AI continue to drive innovation intelligence/articles/10.3389/frai.2024.1297347/pdf
in sign language technology, including real-time
translation, avatar-based signing, and personalized [11] Public Awareness Campaigns for Sign Language
learning tools. Adoption by K. Wilson (2022):
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC811
VI. Conclusion 3838/
Breaking communication barriers for the deaf community
requires a holistic approach that integrates technological [12] Integration of AR Technologies in Deaf Education by J.
innovation with socio-cultural advocacy. While significant Huang (2019): https://www.mdpi.com/2227-
progress has been made, challenges remain in achieving 7080/11/4/83
universal access to sign language systems and fostering
inclusivity. By prioritizing research, education, and policy [13] Policy Recommendations for Inclusive Workplaces by
M. Taylor (2020): [invalid URL removed]
reforms, we can create a future where sign language is not
only recognized but celebrated as an integral part of human [14] Improving UX in Assistive Communication Devices by
communication. E. Robinson (2021):
https://www.frontiersin.org/journals/artificial-
References intelligence/articles/10.3389/frai.2024.1297347/pdf
[1] Machine Learning Approaches to Sign Language
Recognition by J. Smith (2021): [15] Neural Networks for Sign Language Recognition by F.
https://www.frontiersin.org/journals/artificial- Khan (2022):
intelligence/articles/10.3389/frai.2024.1297347/pdf https://www.frontiersin.org/journals/artificial-
intelligence/articles/10.3389/frai.2024.1297347/pdf
[2] Advances in Sign Language Translation Technologies
by R. Patel and V. Kumar (2020): [16] Expanding Sign Language Datasets for AI by D. Lopez
https://www.mdpi.com/2227-7080/11/4/83 (2020): https://www.mdpi.com/2227-7080/11/4/83
[3] Cultural Barriers in Deaf Communication by P. [17] Media Representation of Deafness by S. Evans
Anderson (2019): (2021):https://www.ncbi.nlm.nih.gov/pmc/articles/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC811 PMC8113838/
3838/
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