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 was a meeting point for researchers and professionals working in translation and interpreting technologies and NLP researchers, enabling them to discuss how NLP techniques can augment and enhance translation of texts and delivery of interpreting. A particular focus of the panel was human-centric technologies meant to support, rather than replace, translators and interpreters. 


Dr Diptesh Kanojia

Diptesh Kanojia

University of Surrey

Constantin Orasan

Constantin Orăsan

University of Surrey