NLP augmenting translation and interpreting

Natural language processing augmenting translation and interpreting

Recent developments in deep learning have led to improvements in many areas of natural language processing (NLP). The advances in machine translation (MT) had a major impact on professional translators and the translation profession. The current state of the art in machine interpreting (MI) has less of an impact on interpreters, but as the technology improves, it is likely to become more relevant in certain scenarios. However, there are many other areas of NLP which already support translators and interpreters, or have the potential to do so. 

This panel seeks to act as a meeting point for researchers and professionals working in translation and interpreting technologies and NLP researchers, with the aim of enabling them to discuss how NLP techniques can augment and enhance translation of texts and delivery of interpreting. The main focus will be on technologies other than MT and MI, but it does not mean these fields will not be discussed. A particular focus of the panel will be on human-centric technologies meant to support, rather than replace, translators and interpreters. 

The panel will start with short presentations from several established researchers who will express their views about the role of NLP in translation and interpreting, and what impacts they have on the translation and interpreting professions. The presentations will be followed by a round table which will further delve into these topics and discuss how NLP researchers and researchers in translation and interpreting technologies can benefit from each other's expertise.


Dr Diptesh Kanojia

Diptesh Kanojia

University of Surrey

Constantin Orasan

Constantin Orăsan

University of Surrey