EXPERT:        EXPERT (EXPloiting Empirical appRoaches to Translation) aims to train young researchers, namely Early Stage Researchers (ESRs) and Experienced Researchers (ERs), to promote the research, development and use of hybrid language translation technologies. The overall objective of EXPERT is to provide innovative research and training in the field of Translation memory and Machine Translation Technologies to 15 Marie Curie Fellows.

MARS:             On-going internal project which develops a knowledge-poor anaphora resolution for English.

PALinkA:        On-going internal project which develops a multipurpose annotation tool.

DVC:                          AHRC-funded project which aimed to discover characteristic patterns of use for English verbs and show how meanings are associated with patterns of word use, rather than words in isolation.

TELL-ME:                   EACEA Lifelong Learning-funded project which aimed to teach vocationally-specific languages to healthcare professionals and help them to communicate at work.

FIRST:                         FP7-funded project which deployed and developed language technology to automatically detect and remove obstacles to reading comprehension for people with Autism Spectrum Disorders.

MESSAGE:                  EU funded project which delivered controlled languages standards for messages, alerts and protocols arising from terrorism and other security related risks in order to ensure correct transmission of understanding and reliable translation where necessary.

AIR:                             Automatic Archiving for an Institutional Repository: A JISC-funded project aimed to develop an information extraction system for discovery and extraction of bibliographical data from semi-structured text.

QALL-ME:                   EU funded project on Question Answering Learning Technologies in a multiLingual and multiModal Environment.

CAID:                          Computer-aided multiple-choice test items development: a project which used NLP technology to provide aids to speed up the process of authoring multiple-choice test items.

REGEN:                       Rapid items generation: a project which used NLP technology to speed up the process of building multiple choice questions.

SYN-CAR:                   Collaborative project funded by British Council on coreference and anaphora resolution with University of Tuebingen.

NP4E:                          British Academy funded project on development of a methodology in the form of detailed annotation schemes and guidelines for marking noun phrase and event coreference within one document and across different documents.

Corpora4Teaching:   CELT funded project with the goal of encouraging staff to use corpora in language teaching.

BiRD:                          The goal of this project was to produce a system which will mine information about resources for different research domains on the Internet, and produce a database that will be accessible online for anyone wishing to exploit it.

CAST:                         The main objective of this project was the research and development of a user-oriented computer-aided summarisation tool. The project also proposed new methods for automatic summarisation and evaluation of automatic summarisation methods. The construction of a corpus with the most important sentences marked and other information useful for summarisation annotated will be an additional product of the project.