Investigating low-resource machine translation for English-to-Tamil
Ramesh, Akshai, Parthasarathy, Venkatesh Balavadhani, Haque, RejwanulORCID: 0000-0003-1680-0099 and Way, AndyORCID: 0000-0001-5736-5930
(2020)
Investigating low-resource machine translation for English-to-Tamil.
In: Proceedings of the 3rd Workshop on Technologies for MT of Low Resource Languages (LoResMT 2020) AACL-IJCNLP, December 4-7, 2020, Suzhou, China (Online).
Statistical machine translation (SMT) which was the dominant paradigm in machine translation (MT) research for nearly three decades has recently been superseded by the end-to-end deep learning approaches to MT. Although deep neural models produce state-of-the-art results in many translation tasks, they are found to under-perform on resource-poor scenarios. Despite some success, none of the present-day benchmarks that have tried to overcome this problem can be regarded as a universal solution to the problem of translation of many low-resource languages. In this work, we investigate the performance of phrase-based SMT (PB-SMT) and neural MT (NMT) on a rarely-tested low-resource language-pair, English-to-Tamil, taking a specialised data domain (software localisation) into consideration.
In particular, we produce rankings of our MT systems via a social media platform-based human evaluation scheme, and demonstrate our findings in the low-resource domain-specific text translation task.
Metadata
Item Type:
Conference or Workshop Item (Paper)
Event Type:
Conference
Refereed:
Yes
Additional Information:
Part of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL) and the 10th International Joint Conference on Natural Language Processing (IJCNLP).
Science Foundation of Ireland, Grant No. 13/RC/2106, European Research Council, European Union’s Horizon 2020 research and innovation programme under the Marie SkłodowskaCurie grant agreement No. 713567, Science Foundation of Ireland, Grant No. 13/RC/2077
ID Code:
25201
Deposited On:
04 Dec 2020 14:23 by
Rejwanul Haque
. Last Modified 07 Jan 2022 16:54