NMT Framework for Verse Translation from Hindi to English with CDEC
In the modern era, AI and ML are highly demanding Technologies. AI and ML are used to train machines and computers to do types of human work or exactly like human beings. With the help of AI and ML people solve real-life problems. “Chat-GPT” is one of the major examples. “Chat-GPT” is an “AI” tool to generate speech and text and it can be manipulated according to them Language translation is one of the important tasks. Because in this world there are uncountable languages is here. And people need to communicate with each other. So, there are many translators present in the market like Google translator, Microsoft Bing Translator, Yandex and many more translators. However, this type of translator translates only the normal text from the source language to the target language. So our research is based on verse(poetic) translation like poems, mythological text etc this type of verse translation is the most challenging task. So our researcher reached the NLP tool named CDEC. Which has already translated the Chinese poem into English and was developed by Cries Dyler this research motive is to run the CDEC and train the verse model from Hindi to the English language. After Completing this task people can translate verse text. All the translated text was analyzed by BLEU Bilingual Evaluation Understudy. This review aims to analyze how to translate verse text from Hindi to English Language with CDEC.
Authors
- Rajesh Kumar Chakrawarti (ORCID: https://orcid.org/0000-0002-5910-271X)
- Nikhlesh Pathik (ORCID: https://orcid.org/0000-0002-3303-8684)
- Puspraj Singh Chauhan (ORCID: https://orcid.org/0000-0002-9223-5733)
- Lucky Jaiswal
Institutions
- Devi Ahilya Vishwavidyalaya (IN)
- Maulana Azad National Institute of Technology (IN)
Publication Details
- Published
- 2025-02-21
- DOI
- https://doi.org/10.1109/ce2ct64011.2025.10939390
- Citations
- 1
- Primary Topic
- Natural Language Processing Techniques
- Type
- article
- Field-Weighted Citation Impact
- 2.48
Funders
- M.P. Council of Science and Technology