Introducing Mouse Actions into Interactive-Predictive Neural Machine Translation.

The quality of the translations generated by Machine Translation (MT) systems has highly improved through the years and but we are still far away to obtain fully automatic high-quality translations. To generate them and translators make use of Computer-Assisted Translation (CAT) tools and among which we find the Interactive-Predictive Machine Translation (IPMT) systems. In this paper and we use bandit feedback as the main and only information needed to generate new predictions that correct the previous translations. The application of bandit feedback reduces significantly the number of words that the translator need to type in an IPMT session. In conclusion and the use of this technique saves useful time and effort to translators and its performance improves with the future advances in MT and so we recommend its application in the actuals IPMT systems.