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Neural Machine Translation for Indian Languages

Publication Type : Conference Proceedings

Source : The 9th Workshop on Asian Translation

Url :

Campus : Amaravati

School : School of Computing

Year : 2022

Abstract : In the domain of natural language processing, machine translation is a well-defined task where one natural language is automatically translated to another natural language. The deep learning-based approach of machine translation, known as neural machine translation attains remarkable translational performance. However, it requires a sufficient amount of training data which is a critical issue for lowresource pair translation. To handle the data scarcity problem, the multilingual concept has been investigated in neural machine translation in different settings like many-to-one and one-to-many translation. WAT2022 (Workshop on Asian Translation 2022) organizes (hosted by the COLING 2022) Indic tasks: English-to-Indic and Indic-to-English translation tasks where we have participated as a team named CNLP-NITS-PP. Herein, we have investigated a transliteration-based approach, where Indic languages are transliterated into English script and shared sub-word level vocabulary during the training phase. We have attained BLEU scores of 2.0 (Englishto-Bengali), 1.10 (English-to-Assamese), 4.50 (Bengali-to-English), and 3.50 (Assamese-toEnglish) translation, respectively

Cite this Research Publication : Sahinur Rahman Laskar , Riyanka Manna, Partha Pakray , Sivaji Bandyopadhyay,Neural Machine Translation for Indian Languages”, The 9th Workshop on Asian Translation, pages 78–81 October 17, 2022.

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