Synopsis
This volume provides an overview of thefield of Hybrid Machine Translation (MT) and presents some of the latestresearch conducted by linguists and practitioners from differentmultidisciplinary areas. Nowadays, most important developments in MT are achievedby combining data-driven and rule-based techniques. These combinationstypically involve hybridization of different traditional paradigms, such as theintroduction of linguistic knowledge into statistical approaches to MT, theincorporation of data-driven components into rule-based approaches, orstatistical and rule-based pre- and post-processing for both types of MTarchitectures. The book is of interest primarily to MTspecialists, but also - in the wider fields of Computational Linguistics,Machine Learning and Data Mining - to translators and managers of translationcompanies and departments who are interested in recent developments concerningautomated translation tools.
