Machine Translation on Dravidian Languages
B. V. Kiranmayee1, Raparthi Sai Priya2, Rayapurthi Vijaya3, Palthiya Suresh4, Regulapati Venkat Goutham5

1Dr. B. V. Kiranmayee, Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad (Telangana), India.
2Palthiya Suresh, Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad (Telangana), India.
3Raparthi Sai Priya, Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad (Telangana), India.
4Rayapurthi Vijaya, Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad (Telangana), India.
5Regulapati Venkat Goutham, Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad (Telangana), India.
Manuscript received on 15 March 2023 | Revised Manuscript received on 22 March 2023 | Manuscript Accepted on 15 May 2023 | Manuscript published on 30 May 2023 | PP: 1-14 | Volume-12 Issue-1, May 2023 | Retrieval Number: 100.1/ijrte.A75380512123 | DOI: 10.35940/ijrte.A7538.0512123

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Abstract: The Dravidian languages are spoken all over the world. Despite their distinctiveness, Dravidian languages haven’t gotten much attention because there aren’t enough resources to handle tasks like translation that require language technology. Since Dravidian languages are largely spoken in southern India, machine translation is necessary. For those who speak these regional languages, this would improve information creation and access. It can be challenging to translate between languages, particularly that of Dravidian, because of lexical divergence, ambiguity, and other, lexical, syntactic and semantic issues. This research looks into a number of machine translation models for different languages, conducts a thorough literature review on the various machine translation techniques from earlier studies, and analyses their methodology. The major objective of this research is to evaluate the viability and effectiveness of a machine translation process for Dravidian languages.
Keywords: Linguistic Rules, Long Term Dependencies, Bilingual Text Corpora, BLEU Metric, Language Embedding, Translation Memory, and Parallel Corpora.
Scope of the Article: Natural Language Processing and Machine Translation