Efficient text summarization method for blind people using text mining techniques

Owing to the phenomenal growth in communication technology, most of us hardly have time to read books. This habit of reading is slowly diminishing because of the busy lives of people. For visually challenged people, the situation is even worse. In order to address this impedes, we develop a better a...

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Bibliographic Details
Published in:	International journal of speech technology Vol. 23; no. 4; pp. 713 - 725
Main Authors:	Basheer, Shakila, Anbarasi, M., Sakshi, Darpan Garg, Vinoth Kumar, V.
Format:	Journal Article
Language:	English
Published:	New York Springer US 01-12-2020
Subjects:	Artificial Intelligence Engineering Signal,Image and Speech Processing Social Sciences Summarizer Text Text ranking algorithm Text-to-speech
Online Access:	Get full text
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Summary:	Owing to the phenomenal growth in communication technology, most of us hardly have time to read books. This habit of reading is slowly diminishing because of the busy lives of people. For visually challenged people, the situation is even worse. In order to address this impedes, we develop a better and more accurate methodology than the existing ones. In this work, in order to save the efforts for reading the complete text every time, we modify the Weighted TF_IDF (Term Frequency Inverse Document Frequency) algorithm to summarize books into relevant keywords. Then, we compare the modified algorithm with that of the existing algorithms of TextRank Algorithm, Luhn’s Algorithm, LexRank Algorithm, Latent Semantic Analysis(LSA). From the comparative analysis, we find that Weighted TF_IDF is an efficient algorithm to automate text summarization and produce an effective summary which is then converted from text to speech. Thus, the proposed algorithm would highly be useful for blind people.
ISSN:	1381-2416 1572-8110
DOI:	10.1007/s10772-020-09712-z