Zeeshan Khan
2021
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Zeeshan Khan
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Kartheek Akella
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Vinay Namboodiri
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C V Jawahar
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
2020
Exploring Pair-Wise NMT for Indian Languages
Kartheek Akella
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Sai Himal Allu
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Sridhar Suresh Ragupathi
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Aman Singhal
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Zeeshan Khan
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C.v. Jawahar
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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.
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Co-authors
- Kartheek Akella 2
- C.V. Jawahar 2
- Vinay Namboodiri 1
- Sai Himal Allu 1
- Sridhar Suresh Ragupathi 1
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