Author Archives: c.orasan

Can Translation Memories afford not to use paraphrasing?

Screen_Shot_2015-05-11_at_16.54.57.resizedResearch carried out in the EXPERT project between researchers from University of Wolverhampton and Saarland University, Germany is being presented at the European Association for Machine Translation 2015 conference. The work shows how paraphrasing can help the task of translators who use translation memories. Continue reading

Manifestospeak: What can linguistic analysis tell us about politicians and their attitudes?

By Patrick Hanks and Sara Može
Research Institute of Information and Language Processing
University of Wolverhampton

No doubt every politically conscious person in Britain has a pretty good idea by now of the main issues selected by the various political parties fighting each other for votes in the upcoming General Election. An obvious way of finding out what those issues are is to read the manifestos of each of the parties.

But linguistic analysis can tell us more than the politicians ever intended to reveal.  Linguists working on the DVC project at the University of Wolverhampton have been using corpus-analysis tools such as Adam Kilgarriff’s Sketch Engine to explore the language used in the manifestos of four parties: Continue reading

1st CFP of the Workshop on Natural Language Processing for Translation Memories (NLP4TM)

The 1st Call for Papers of the Workshop on Natural Language Processing for Translation Memories (NLP4TM) organised at RANLP 2015 by Constantin Orasan and Rohit Gupta has been published. Information about the topics addressed by the workshop and important dates can be found on the workshop’s webpage.

Measures of collocational strength and flexibility for the identification of MWEs

Dr Michael Oakes is in Malta presenting a poster at PARSEME 4th general meeting in Malta on the topic of Measures of collocational strength and flexibility for the identification of MWEs. The work is done in collaboration with Prof. Patrick Hanks and Dr. Ismail El Maarouf, and uses data created in the DVC project.