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    <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.</abstract>
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%0 Conference Proceedings
%T INMT: Interactive Neural Machine Translation Prediction
%A Santy, Sebastin
%A Dandapat, Sandipan
%A Choudhury, Monojit
%A Bali, Kalika
%Y Padó, Sebastian
%Y Huang, Ruihong
%S Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong, China
%F santy-etal-2019-inmt
%X 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.
%R 10.18653/v1/D19-3018
%U https://aclanthology.org/D19-3018
%U https://doi.org/10.18653/v1/D19-3018
%P 103-108

Markdown (Informal)

[INMT: Interactive Neural Machine Translation Prediction](https://aclanthology.org/D19-3018) (Santy et al., EMNLP-IJCNLP 2019)

• INMT: Interactive Neural Machine Translation Prediction (Santy et al., EMNLP-IJCNLP 2019)

ACL

• Sebastin Santy, Sandipan Dandapat, Monojit Choudhury, and Kalika Bali. 2019. INMT: Interactive Neural Machine Translation Prediction. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations, pages 103–108, Hong Kong, China. Association for Computational Linguistics.