ADAPTIVE CONTEXT-DEPENDENT MACHINE TRANSLATION FOR HETEROGENEOUS TEXT

Grant number: FT130101105 | Funding period: 2014 - 2019

Completed

Abstract

While automatic machine translation technologies are undoubtedly useful to a wide range of users, they often produce incoherent outputs for many types of input, for example, medical, literature, or even conversational text. This project will develop new adaptive machine translation systems to handle many domains and text styles, including heterogeneous mixed-domain inputs. It will develop multi-task machine learning methods for training collections of domain-specific translation systems while leveraging correlations between domains. This approach will reduce the big data requirements of current translation systems, and improve translation quality across a wide range of different language pai..

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Researchers