Abstract
In this paper, we demonstrate an Interactive Machine Translation interface, that assists human translators with on-the-fly hints and suggestions. This makes the end-to-end translation process faster, more efficient, and creates high-quality translations. We augment the OpenNMT backend with a mechanism to accept the user input and generate conditioned translations.
Cite
CITATION STYLE
Santy, S., Dandapat, S., Choudhury, M., & Bali, K. (2019). INMT: Interactive neural machine translation prediction. In EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Proceedings of System Demonstrations (pp. 103–108). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/D19-3018
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