Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/3443
Title: "Talking Books" : A Sinhala Abstractive Text Summarization Approach for Sinhala Textbooks
Authors: Rathnayake, B.R.M.S.R.B.
Manathunga, K
Kasthurirathna, D
Keywords: Summarization
Google-AI
GPT3
Abstractive Summary
Issue Date: 23-May-2023
Publisher: IEEE
Citation: B. R. M. S. R. B. Rathnayake, K. Manathunga and D. Kasthurirathna, ""Talking Books" : A Sinhala Abstractive Text Summarization Approach for Sinhala Textbooks," 2023 IEEE 8th International Conference for Convergence in Technology (I2CT), Lonavla, India, 2023, pp. 1-6, doi: 10.1109/I2CT57861.2023.10126205.
Series/Report no.: 2023 IEEE 8th International Conference for Convergence in Technology (I2CT);
Abstract: The ability for books to talk would be an exciting concept, and this research discussion paves the path for an identical approach. The research objectives discussed in this paper address several burning problems, solve them and adapt them to future technological enhancements from a Sri Lankan context. Burning problems include reducing printing costs for textbooks, addressing students’ health, promoting green technology, and identifying a suitable summarising approach to the native language, Sinhala resulting in students’ learning ease. Other symptoms for the betterment indicate paths taken to reduce the weight of school bags carried by students, reduce paper usage by the government on printing textbooks, and spread technological awareness to teenagers regarding e-Learning. Textbooks issued by the government will be digitized and centralized into a single system that the government officials themselves can administer. The paper discusses limited hindsight literature and proposes 2 new algorithms for abstractive and extractive summarization for Sinhala text. The 2 algorithms are compared against one another in terms of performance, efficiency, precision and accuracy. Experts in the education domain have verified the derived summary of both algorithms. The deliverable artefacts are the mobile application, a RESTful auto-summarization plugin service, and new data sets extracted to train the GPT-3 models.
URI: https://rda.sliit.lk/handle/123456789/3443
ISBN: 979-8-3503-3401-2
Appears in Collections:Department of Computer Science and Software Engineering

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