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Speech to text conversion and summarization for effective understanding and documentation

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 9 No. 5 (2019)

DOI
10.11591/ijece.v9i5.pp3642-3648
ISSN
2722-2578, 2088-8708
Published
2019-10-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Speech, is the most powerful way of communication with which human beings express their thoughts and feelings through different languages. The features of speech differs with each language. However, even while communicating in the same language, the pace and the dialect varies with each person. This creates difficulty in understanding the conveyed message for some people. Sometimes lengthy speeches are also quite difficult to follow due to reasons such as different pronunciation, pace and so on. Speech recognition which is an inter disciplinary field of computational linguistics aids in developing technologies that empowers the recognition and translation of speech into text. Text summarization extracts the utmost important information from a source which is a text and provides the adequate summary of the same. The research work presented in this paper describes an easy and effective method for speech recognition. The speech is converted to the corresponding text and produces summarized text. This has various applications like lecture notes creation, summarizing catalogues for lengthy documents and so on. Extensive experimentation is performed to validate the efficiency of the proposed method

Collaboration network of the authors

3 authors · 2 co-authorship links

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  • Christ University
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Jinsi JoseChrist University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Speech to text conversion and summarization for effective understanding and documentation</dc:title><dc:creator>A, Vinnarasu</dc:creator><dc:creator>Jose, Deepa V</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;p class="western" style="margin-top: 0.21cm; margin-bottom: 0cm;" align="justify"&amp;gt;&amp;lt;span&amp;gt;Speech, is the most powerful way of communication with which human beings express their thoughts and feelings through different languages. The features of speech differs with each language. However, even while communicating in the same language, the pace and the dialect varies with each person. This creates difficulty in understanding the conveyed message for some people. Sometimes lengthy speeches are also quite difficult to follow due to reasons such as different pronunciation, pace and so on.   Speech recognition which is an inter disciplinary field of computational linguistics aids in developing technologies that empowers the recognition and translation of speech into text. Text summarization extracts the utmost important information from a source which is a text and provides the adequate summary of the same. The research work presented in this paper describes an easy and effective method for speech recognition. The speech is converted to the corresponding text and produces summarized text. This has various applications like lecture notes creation, summarizing catalogues for lengthy documents and so on. Extensive experimentation is performed to validate the efficiency of the proposed method&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2019-10-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v9i5.pp3642-3648</dc:identifier><dc:identifier>10.11591/ijece.v9i5.pp3642-3648</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 9 No 5 (2019); 3642</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/17795/12961</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>