Automatic translation is an undeniable need in a globalized world where communication using several languages becomes increasingly more relevant. Translation Memory (TM) and Machine Translation (MT) systems are the two most elaborate technologies to support human translation. Recent developments in the area of Example-based and Statistical Machine Translation (EBMT and SMT), in particular, have shown the potential of data-driven approaches for producing fast and low cost translations. A number of user studies have however established shortcomings in the state-of-the-art of these technologies, including poor quality translations for low resource languages, interfaces that do not take into account user requirements and user feedback, etc.
We propose the creation of an Initial Training Network to train young researchers on ways to improve current data-driven MT technologies (TM, SMT and EBMT) by exploiting their individual strengths through their combination and by addressing some of the main limitations of each of these technologies. Leading academic and industrial partners in all data-driven translation technologies, along with both professional translators and end-users of translation technologies will support young researchers of the network during the whole research and development cycle, providing guidance, core and complementary training skills and evaluating the resulting technologies. A comprehensive set of training materials on core and complementary skills developed during this project will be made freely available to other researchers interested in the field. We expect the training of researchers in the new skills required for the development and use of technologies that can increase productivity and reduce costs in the translation sector, as well as facilitate reliable communication and content creation in multiple languages, will contribute to several aspects of Europes ICT development.

Linguistic diversity is a corner stone of our multicultural European society. To preserve this essential asset in the age of the emerging information and knowledge society, Europe needs ICT technologies and applications at affordable costs that enable communication, collaboration and participation across language boundaries secure their language users equal access to the information and knowledge society support each language in the advanced functionalities of networked ICT Prerequisites of these applications are advances in several fields of Human Language Technologies (HLT) such as machine translation (MT) including automatic translation and machine assisted human translation technologies for information and knowledge management including IR, crosslingual IR and corporate memories technologies for document and content production and management (including authoring tools, language checking and interactive content applications) technologies for intuitive interfaces to all types of technology (including multimodal user interfaces, speech interfaces for interactive mobile applications, robot control interfaces) Building a single EU information space reflecting and supporting the cultural diversity of our continent as an adequate foundation for the multilingual European information and knowledge society is a major challenge.

Because of the complexity of human language and the number of languages to be included this challenge demands a large collective effort of research and language communities as well as several industrial sectors. T4ME shall seek progress by approaching open problems in collaboration with other research fields such as machine learning, social computing, cognitive systems, knowledge technologies and multimedia content. It shall mobilize and strengthen the European HLT community encompassing researchers, developers and language professionals through networking of research and by creating new schemes of sharing resources and efforts.

Europe faces a growing economic and societal challenge due to its vast diversity of languages, and machine translation (MT) technology holds promise as a means to address this challenge.

EuroMatrix Plus will
- continue the rapid advance of MT technology, creating example systems for every official EU language, and providing other MT developers with our infrastructure for building statistical translation models,
- continue and broaden the controlled systematic investigation of different approaches and techniques to accelerate the scientific evolution of novel methods, including both selection and crossfertilization. The aim is to arrive at scientifically well understood novel combinations of methods that are proven superior to the state of the art,
- contribute to the growth and competitiveness of the European MT research scene and infrastructure through open evaluations and living community supported surveys of resources, tools, systems and their respective capabilities,
- focus on bringing MT to the users, in addition to focusing on scientific advances.

Because our statistical models are derived from example translations, we can build and exploit a synergistic relationship in which users suggest improvements to the system by post-editing its output, and the system improves itself by learning from user feedback.

EuroMatrix Plus focuses on two types of users: professional translators and translation agencies working for private corporations, administrations, and other organisations, and lay users who create content on a volunteer basis by translating foreign materials into their own languages. We will investigate how these users can benefit from state of the art in MT, and conversely, how MT can benefit from user corrections, and create an openly accessible sample application that enables users to automatically translate news stories and web pages from any EU language into any other, and whose corrections will be exploited for improving MT technology.