A Method to Integrate Word Sense Disambiguation and Translation Memory for English to Hindi Machine Translation System

  • Sunita Rawat Shri Ramdeobaba College of Engineering and Management

Abstract

Word sense disambiguation deals with deciding the word’s precise meaning in a certain specific context. One of the major problems in natural language processing is lexicalsemantic ambiguity, where a word has more than one meaning. Disambiguating the sense of polysemous words is the most important task in machine translation. This research work aims to design and implement English to Hindi machine translation. The design methodology addresses improving the speed and accuracy of the machine translation process. The algorithm and modules designed in this research work have been deployed on the Hadoop infrastructure, and test cases are designed to check the feasibility and reliability of this process. The research work presented describes the methodologies to reduce data transmission by adding a translation memory component to the framework. The speed of execution is increased by replacing the modules in the machine translation process with lightweight modules, which reduces infrastructure and execution time.

Keywords

machine translation, word sense disambiguation, statistical machine translation, translation memory,

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Published
Apr 11, 2022
How to Cite
RAWAT, Sunita. A Method to Integrate Word Sense Disambiguation and Translation Memory for English to Hindi Machine Translation System. Computer Assisted Methods in Engineering and Science, [S.l.], v. 29, n. 1–2, p. 125–144, apr. 2022. ISSN 2956-5839. Available at: <https://cames.ippt.pan.pl/index.php/cames/article/view/395>. Date accessed: 15 nov. 2024. doi: http://dx.doi.org/10.24423/cames.395.