Bishwaraj Paul


2021

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Neural Machine Translation for Tamil–Telugu Pair
Sahinur Rahman Laskar | Bishwaraj Paul | Prottay Kumar Adhikary | Partha Pakray | Sivaji Bandyopadhyay
Proceedings of the Sixth Conference on Machine Translation

The neural machine translation approach has gained popularity in machine translation because of its context analysing ability and its handling of long-term dependency issues. We have participated in the WMT21 shared task of similar language translation on a Tamil-Telugu pair with the team name: CNLP-NITS. In this task, we utilized monolingual data via pre-train word embeddings in transformer model based neural machine translation to tackle the limitation of parallel corpus. Our model has achieved a bilingual evaluation understudy (BLEU) score of 4.05, rank-based intuitive bilingual evaluation score (RIBES) score of 24.80 and translation edit rate (TER) score of 97.24 for both Tamil-to-Telugu and Telugu-to-Tamil translations respectively.