Lack of sufficient linguistic resources for many languages and domains currently is one of the major obstacle in further advancement of automated translation. The main goal of the ACCURAT research is to find, analyze and evaluate novel methods how comparable corpora can compensate for this shortage of linguistic resources to improve MT quality significantly for under-resourced languages and narrow domains.The ACCURAT project will provide researchers and developers with novel methodology and fully functional model for exploiting comparable corpora to increase translation quality of existing and emerging MT systems.We will determine criteria to measure the comparability of texts in comparable corpora. Methods for automatic acquisition of a comparable corpus from the Web will be analyzed and evaluated. Advanced techniques will be elaborated to extract lexical, terminological and other linguistic data from comparable corpora to provide training and customization data for MT. Improvements from applying acquired data will be measured against baseline results from MT systems and validated in practical applications.ACCURAT will provide novel approaches to achieve high quality MT translation for a number of under-resourced EU languages (e.g. Estonian, Croatian) and to adapt existing MT technologies to narrow domains (e.g. automotive engineering), significantly increasing the language and domain coverage of MT. ACCURAT methods will be universal and adaptable to new languages and domains.The project consortium has an optimum balance of world-class researchers in all key research areas and industry SME participants ensuring maximum orientation to exploitation needs.The ACCURAT will provide contribution for expected impacts of the Call by providing methods for automatic acquisition and annotation of language resources, removing gaps in language coverage and increasing quality of translation and providing methods for automated translation to make it more adaptive.