Multi-modal and Language Technology Based Post-Editing Support for Machine Translation

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General Information

In order to ensure professional human quality level translation results, in many cases, the output of Machine Translation (MT) systems has to be manually post-edited by human experts. The postediting process is carried out within a post-editing (PE) environment, a user-interface, which supports the capture and correction of mistakes, as well as the selection, manipulation, adaptation and recombination of good segments. PE is a complex and challenging task involving considerable cognitive load. To date, PE environments mostly rely on traditional graphical user interfaces (GUIs), involving a computer screen as display and keyboard and mouse as input devices. In this research project we propose the design, development, implementation and extensive road-testing and evaluation of a novel multi-modal post-editing support for machine translation for translation professionals, which extends traditional input techniques of a PE system, such as keyboard and mouse, with novel free-hand and screen gestures, as well as speech and gaze input modalities (and their combinations). The objectives of the research are to increase the usability and the user experience of post-editing Machine Translation and to reduce the overall cognitive load of the translation task, supporting (i) the core post-editing tasks as well as (ii) controlling the PE system and environment. The multimodal PE environments will be integrated with quality prediction (QE) to automatically guide search for useful segments and mistakes, as well as automatic PE via incremental adaptation of MT to PEs to avoid repeat mistakes, in order to achieve the above mentioned objectives. The environments will be road-tested with human translation professionals and trainees and (where possible) within the partner projects in the Paketantrag (Riezler, Frazer, Ney and Waibel) and (where possible) the post-edited data captured will feed into dynamic and incremental MT retraining and update approaches pursued in the partner projects.



Project Start

01/03/2017: The project officially started.


Santanu Pal

Santanu Pal

Postdoctoral Researcher

Nico Herbig

Nico Herbig

Doctoral Researcher

Josef van Genabith

Josef van Genabith

Professor for Multilingual Technologies

Antonio Krüger

Antonio Krüger

Professor for Human Computer Interaction


Multi-modal CAT


Neural Automatic Post-Editing Using Prior Alignment and Reranking

Pal, S., Naskar, S. K., Vela, M., Liu, Q., & van Genabith, J. (2017). EACL 2017, 349.

CATaLog Online: A Web-based CAT Tool for Distributed Translation with Data Capture for APE and Translation Process Research

Pal, S., Naskar, S. K., Zampieri, M., Nayak, T., & van Genabith, J. (2016). In COLING (Demos) (pp. 98-102).

Multi-Engine and Multi-Alignment Based Automatic Post-Editing and its Impact on Translation Productivity

Pal, S., Naskar, S. K., & van Genabith, J. (2016). In COLING (pp. 2559-2570).

A neural network based approach to automatic post-editing

Pal, S., Naskar, S. K., Vela, M., & van Genabith, J. (2016, August). In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Vol. 2, pp. 281-286).

CATaLog Online: Porting a Post-editing Tool to the Web

Pal, S., Zampieri, M., Naskar, S. K., Nayak, T., Vela, M., & van Genabith, J. (2016, May). In LREC.

CATaLog: New approaches to tm and post editing interfaces

Nayek, T., Naskar, S. K., Pal, S., Zampieri, M., Vela, M., & van Genabith, J. (2015). RANLP 2015, 36.

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