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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 1, 2021.
Abstract: Gujarati language is the Indo-Aryan language spoken by the Gujaratis, the people of the state of Gujarat of India. Gujarati is the one of the 22 official languages recognized by the Indian government. Gujarati script was adopted from Devanagari script. Approximately 3000 idioms are available in Gujarati language. Machine translation of any idiom is the challenging task because contextual information is important for the translation of a particular idiom. For the translation of Gujarati idioms into English or any other language, surrounding contextual words are considered for the translation of specific idiom in the case of ambiguity of the meaning of idiom. This paper experiments the IndoWordNet for Gujarati language for getting synonyms of surrounding contextual words. This paper uses n-gram model and experiments various window sizes surrounding the particular idiom as well as role of stop-words for correct context identification. The paper demonstrates the usefulness of context window in case of ambiguity in the meaning identification of idioms with multiple meanings. The results of this research could be consumed by any destination-independent machine translation system for Gujarati language.
Jatin C. Modh and Jatinderkumar R. Saini, “Using IndoWordNet for Contextually Improved Machine Translation of Gujarati Idioms” International Journal of Advanced Computer Science and Applications(IJACSA), 12(1), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120128
@article{Modh2021,
title = {Using IndoWordNet for Contextually Improved Machine Translation of Gujarati Idioms},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120128},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120128},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {1},
author = {Jatin C. Modh and Jatinderkumar R. Saini}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.