Kartheek Akella


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More Parameters? No Thanks!
Zeeshan Khan | Kartheek Akella | Vinay Namboodiri | C V Jawahar
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021


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Exploring Pair-Wise NMT for Indian Languages
Kartheek Akella | Sai Himal Allu | Sridhar Suresh Ragupathi | Aman Singhal | Zeeshan Khan | C.v. Jawahar | Vinay P. Namboodiri
Proceedings of the 17th International Conference on Natural Language Processing (ICON)

In this paper, we address the task of improving pair-wise machine translation for specific low resource Indian languages. Multilingual NMT models have demonstrated a reasonable amount of effectiveness on resource-poor languages. In this work, we show that the performance of these models can be significantly improved upon by using back-translation through a filtered back-translation process and subsequent fine-tuning on the limited pair-wise language corpora. The analysis in this paper suggests that this method can significantly improve multilingual models’ performance over its baseline, yielding state-of-the-art results for various Indian languages.