Abstract
An Artificial Intelligence (AI)-based scribe known as L &E Refiner for blind learners is a technology that utilizes natural language processing and machine learning techniques to automatically transcribe lectures, books, and other written materials into audio format. This system is designed to provide an accessible learning experience for blind students, allowing them to easily access and interact with educational content. The AI scribe is able to recognize and understand various forms of text, including handwriting, printed text, and digital documents, and convert them into speech output that blind learners easily comprehend. This technology has the potential to significantly improve the accessibility and inclusion of education for blind individuals.
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References
Ali SA (2023) Artificial intelligence techniques to understand braille: a language for visually impaired individuals. In: Handbook of research on artificial intelligence applications in literary works and social media. IGI Global, pp 254–276
Bharadwaj KA, Joshi MM, Kumbale NS, Shastry NS, Panimozhi K, Choudhury AR (2020) Speech automated examination for visually impaired students. In: 2020 2nd international conference on innovative mechanisms for industry applications (ICIMIA). IEEE, pp 378–381
Dhou S, Alnabulsi A, Al-Ali A, Arshi M, Darwish F, Almaazmi S, Alameeri R (2022) An IoT machine learning-based mobile sensors unit for visually impaired people. Sensors 22(14):5202
Fernandes DL, Ribeiro MHF, Cerqueira FR, Silva MM (2022) Describing image focused in cognitive and visual details for visually impaired people: an approach to generating inclusive paragraphs. arXiv preprint arXiv:2202.05331
Ghatwary N, Abouzeina A, Kantoush A, Eltawil B, Ramadan M, Yasser M (2022) Intelligent assistance system for visually impaired/blind people (ISVB). In: 2022 5th international conference on communications, signal processing, and their applications (ICCSPA). IEEE, pp 1–7
Jadhav A, Padwad H, Chandak M, Raut R (2022) Use of assistive techniques for the visually impaired people. Intelligent systems for rehabilitation engineering, pp 115–127
Mina PNR, Solon IM, Sanchez FR, Delante TK, Villegas JK, Basay FJ, Andales Jr, Pasko F, Estrera MFR, Samson Jr, R et al (2023) Leveraging education through artificial intelligence virtual assistance: a case study of visually impaired learners. Int J Educ Innov Res 2(1):10–22
Mukhiddinov M, Djuraev O, Akhmedov F, Mukhamadiyev A, Cho J (2023) Masked face emotion recognition based on facial landmarks and deep learning approaches for visually impaired people. Sensors 23(3):1080
Rajan R, Devasena MG (2022) A novel reading technique for visually impaired person using enhanced optical character recognition method. NEUROQUANTOLOGY 20(12):634–650
Xue K, Barker E (2022) Using artificial intelligence (AI) to improve math accessibility for students with visual impairments. Technical brief. NWEA
Yoon I, Mathur U, Gibson B, Fazli TP, Miele J (2019) Video accessibility for the visually impaired. In: International conference on machine learning AI for social good workshop, vol 1, p 1
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Vinay, M., Jayapriya, J. (2024). Artificial Intelligence-Based L&E-Refiner for Blind Learners. In: Joshi, A., Mahmud, M., Ragel, R.G., Karthik, S. (eds) ICT: Innovation and Computing. ICTCS 2023. Lecture Notes in Networks and Systems, vol 879. Springer, Singapore. https://doi.org/10.1007/978-981-99-9486-1_36
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DOI: https://doi.org/10.1007/978-981-99-9486-1_36
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