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Volume 08 Issue 03 March 2025

AI-Driven Assistive Technology for Speech Disabilities: Transforming Communication with Natural Language Processing Techniques
1Dr. Vandana Kalra, 2*Dr. Supreet Kaur Sahi, 3Yajat Kohli
1Associate Professor, Department of Computer Science, Sri Guru Gobind Singh College of Commerce, University of Delhi
2*Assistant Professor (Corresponding Author), Department of Computer Science, Sri Guru Gobind Singh College of Commerce, University of Delhi
3Student, B.Sc(H)Computer Science, Sri Guru Gobind Singh College of Commerce, University of Delhi
Corresponding Author: Dr. Supreet Kaur Sahi
DOI : https://doi.org/10.47191/ijmra/v8-i03-05

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ABSTRACT:

Speech disabilities are considered a core barrier to achieving effective communication, independence and social engagement, and therefore assistive devices are needed which are unconventional and fit a myriad of complex user requirements. Many people often have nonstandard speech and assistive devices usually do not cater to their needs hence their ability to use such devices gets compromised. This research suggests that deep learning techniques such as reinforcement learning and model founded approaches like BERT and GPT should be incorporated. Also, the scientists recommend a combination of feedbacks systems with real-time tailoring and individualization. Such integration can qualify individuals to use previously challenging semi-automated systems without restrictions. It provides that view of systems which uses Artificial Intelligence (AI) and generates user’s intent prediction alongside conversion of text to speech that sounds natural to the user. Considering the need for broader and inclusive solutions, the research discusses key issues of how to ensure cost-efficient and easy training of users in order to remove barriers to using assistive technologies. Through novel and sweeping changes, this research aims to further the understanding of how the autonomy and quality of life for people with speech disabilities can be greatly improved.

KEYWORDS:

Text-to-Speech, Intent Recognition Systems, Natural Language processing, Speech disabilities, Communication, Reinforcement Learning

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3) Kakarwal S, Paithane P, Khedikar S. Review: Natural Language Processing and Speech Signal for Mental Health Research and Care Application.; 2020. doi:10.35629/5252-0205786789

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10) Matre ME, Cameron DL. A scoping review on the use of speech-to-text technology for adolescents with learning difficulties in secondary education. Disability and Rehabilitation: Assistive Technology. 2024;19(3):1103-1116. doi:10.1080/17483107.2022.2149865

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Volume 08 Issue 03 March 2025

There is an Open Access article, distributed under the term of the Creative Commons Attribution – Non Commercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/), which permits remixing, adapting and building upon the work for non-commercial use, provided the original work is properly cited.


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