Page 277 - Emerging Trends and Innovations in Web-Based Applications and Technologies

International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
solutions aim to empower individuals with hearing and accessibility: Immersive learning systems.
impairments by providing them with robust tools that enable Advances in Human-Computer Interaction, 2021.
more inclusive and meaningful interactions in social, DOI:10.1155/2021/6693415https://dl.acm.org/doi/
educational, and professional settings. 10.1145/3529836.3529943
Future advancements in this field will prioritize global [8] Sign Language NLP and Translation Models, Camgoz,
inclusivity by ensuring support for diverse sign languages, N. C., et al. (2020). Sign language transformers: A
promoting accessibility across regions, and accommodating neural network approach for translation. IEEE
cultural nuances. Scalability will also be a central focus, with Transactions on Pattern Analysis and Machine
efforts directed toward enhancing system performance in Intelligence.
real-time scenarios and expanding applications to larger DOI:10.1109/TPAMI.2020.3041418https://arxiv.org/
audiences. Additionally, research will address the abs/2009.03988
adaptability of these systems to evolving cultural and [9] De Meulder, M., & Murray, J. J. (2017). Recognizing
linguistic trends, ensuring that they remain relevant and sign languages as languages: Perspectives from
effective across various contexts. linguistics and policy. Language Policy, 16(4), 423-
442. DOI:10.1007/s10993-016-9415-5
Ultimately, these innovations will not only serve as
indispensable tools for the deaf community but also foster a [10] Shen, J., et al. (2018). Natural TTS synthesis by
society that values equality, empathy, and understanding. By conditioning WaveNet on mel spectrogram
continuing to refine and expand these technologies, predictions.
researchers and practitioners can contribute to a future [11] IEEE International Conference on Acoustics, Speech
where communication barriers are significantly reduced, and and Signal Processing (ICASSP), 4779-4783.
every individual has the opportunity to connect and thrive. DOI:10.1109/ICASSP.2018.8461368
VIII. REFERENCES Ø Journal Articles
[1] Glove Translating Sign Language to Speech, Jun- [1] Camgoz, N. C., Koller, O., Hadfield, S., & Bowden, R.
Cheng, W., et al. (2020). Wearable sign-to-speech (2020). Sign language transformers: A neural network
translator glove: Real-time gesture recognition and approach for translation. IEEE Transactions on
spoken translation. Sensors and Actuators, B: Pattern Analysis and Machine Intelligence.
Chemical, 318. DOI:10.1109/TPAMI.2020.3041418
DOI:10.1016/j.snb.2020.128877https://people.ece.co [2] Fang, L., Liu, M., & Chen, H. (2021). Virtual reality for
rnell.edu/land/courses/ece4760/FinalProjects/f2014 sign language education and accessibility: Immersive
/rdv28_mjl256/webpage/ learning systems. Advances in Human-Computer
[2] AI-Powered Sign Language Recognition. Zisserman, A., Interaction. DOI:10.1155/2021/6693415
&Awad, G. (2018). Sign Language Recognition with [3] Koller, O., Ney, H., & Bowden, R. (2020). Large-scale
Temporal Convolutional Networks. Proceedings of the continuous sign language recognition. International
European Conference on Computer Vision Journal of Computer Vision, 128(5), 1323-1341.
(ECCV).Retrieved from ECCV Conference Papers. DOI:10.1007/s11263-019-01258-4
https://pubmed.ncbi.nlm.nih.gov/34502733/ Ø Reports
[3] Sign Language Datasets and Augmentation [1] State of Accessibility in Artificial Intelligence: Bridging
Techniques, Koller, O., et al. (2020). RWTH-PHOENIX- the Gap for Deaf Communities. Published by World
Weather 2014T: Extensions and improvements in Federation of the Deaf (WFD), 2021.www.wfdeaf.org
large-scale sign language recognition. International [2] Technological Innovations in Deaf Education:
Journal of Computer Vision, 128(5), 1323-1341. Opportunities and Challenges. UNESCO Report on
DOI:10.1007/s11263-019-01258-4 Inclusion and Technology, 2022.UNESCO Technology
[4] Multimodal Approaches to Gesture Recognition, Sahu, & Inclusion Report
A., et al. (2022). Leveraging multimodal data for sign Ø Websites
language translation: Combining vision, audio, and [1] SignAll – A company developing sign language
contextual processing. IEEE Transactions on translation technology .Website: https://signall.us
Multimedia, 24(1), 104-118. [2] Hand Talk – AI-powered solutions for sign language
DOI:10.1109/TMM.2022.3171231 recognition and translation. Website:
[5] Speech Synthesis for Deaf Accessibility, Shen, J., et al. https://www.handtalk.me
(2018). Natural TTS synthesis by conditioning [3] Gallaudet University – Research on accessibility and
WaveNet on mel spectrogram predictions. IEEE AI in deaf communities. Website:
International Conference on Acoustics, Speech and https://www.gallaudet.edu
Signal Processing (ICASSP), 4779-4783. Ø Online Articles
DOI:10.1109/ICASSP.2018.8461368https://academic. [1] "Wearable-Tech Glove Translates Sign Language into
oup.com/jdsde/article/11/1/94/410770 Speech in Real Time" UCLA Samueli Newsroom,
[6] Cultural and Linguistic Diversity in Sign Language 2020.https://samueli.ucla.edu/wearable-tech-glove-
Research, DeMeulder, M., & Murray, J. J. (2017). translates-sign-language-into-speech-in-real-time/
Recognizing sign languages as languages: Perspectives [2] "How AI is Transforming Sign Language Recognition"
from linguistics and policy. Language Policy, 16(4), Forbes Technology Council, 2022.
423-442. DOI:10.1007/s10993-016-9415-5 [3] "Advances in Sign Language Technology: From
[7] Virtual Reality for Sign Language Learning, Fang, L., et Translation to Accessibility" MIT Technology Review,
al. (2021). Virtual reality for sign language education 2021.

IJTSRD | Special Issue on Emerging Trends and Innovations in Web-Based Applications and Technologies Page 267