JOURNAL ARTICLE

Speech to text conversion and summarization for effective understanding and documentation

A VinnarasuDeepa Jose

Year: 2019 Journal:   International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering Vol: 9 (5)Pages: 3642-3642   Publisher: Institute of Advanced Engineering and Science (IAES)

Abstract

<p class="western" style="margin-top: 0.21cm; margin-bottom: 0cm;" align="justify"><span>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</span></p>

Keywords:
Automatic summarization Pronunciation Computer science Pace Speech translation Documentation Natural language processing Field (mathematics) Speech recognition Artificial intelligence Linguistics Machine translation

Metrics

43
Cited By
1.08
FWCI (Field Weighted Citation Impact)
20
Refs
0.83
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Speech Recognition and Synthesis
Physical Sciences →  Computer Science →  Artificial Intelligence
Natural Language Processing Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence

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