Exploiting data-driven hybrid approaches to translation in the EXPERT project Constantin Or˘ asan 1 , Carla Parra Escart´ ın 2 , Lianet Sep´ ulveda Torres 3 , Eduard Barbu 4 1 University of Wolverhampton, United Kingdom; 2 ADAPT Centre, Dublin City University, Ireland; 3 Pangeanic, Spain 4 University of Tartu, Estonia C.Orasan@wlv.ac.uk, carla.parra@adaptcentre.ie, lisepul@gmail.com, eduard.barbu@ut.ee August 2, 2018 Abstract Researchers working in machine translation have benefited from the availability of large-scale corpora, and as a result in recent years an increasing number of empirical methods have been proposed. This chapter presents a brief overview of EXPERT (EXPloiting Empirical appRoaches to Translation), an FP7 EC-funded project whose main aim was to promote the research, development and use of data- driven hybrid language translation technology. Given the importance of translation memories in the everyday activities of professional translators, the chapter presents three research directions pursued in EXPERT which aimed to develop data-driven tools that are directly useful for translators. 11.1 Introduction Technologies have transformed the way we work and this is also applicable to the translation industry. In the past 30-35 years, professional translators have experienced an increased technification of their work. Barely 30 years ago, a professional translator would not receive a translation assignment attached to an e-mail or via an FTP and yet, for the younger generation of professional translators receiving an assignment by electronic means is the only reality they know. In addition, as pointed out in several works such as Folaron [2010] and Kenny [2011], professional translators now have a myriad of tools available to use in the translation process.