Learning from Post-Editing: Online Model Adaptation for Statistical Machine Translation

Post-\'edition statistique pour l'adaptation aux domaines de sp\'ecialit\'e en traduction automatique (Statistical Post-Editing of Machine Translation for Domain Adaptation) [in French]

A Post-editing Interface for Immediate Adaptation in Statistical Machine Translation

Adaptive machine translation (MT) systems are a promising approach for improving the effectiveness of computer-aided translation (CAT) environments. There is, however, virtually only theoretical work that examines how su…

A User-Study on Online Adaptation of Neural Machine Translation to Human Post-Edits

The advantages of neural machine translation (NMT) have been extensively validated for offline translation of several language pairs for different domains of spoken and written language. However, research on interactive …

Incremental Adaptation of NMT for Professional Post-editors: A User Study

A common use of machine translation in the industry is providing initial translation hypotheses, which are later supervised and post-edited by a human expert. During this revision process, new bilingual data are continuo…

Online Learning over Time in Adaptive Neural Machine Translation

Adaptive Machine Translation purports to dynamically include user feedback to improve translation quality. In a post-editing scenario, user corrections of machine translation output are thus continuously incorporated int…