The European Association for Machine Translation (EAMT) invites everyone interested in machine translation, translation-related tools and resources to participate in this conference.
The EAMT invites entries for its 2017 EAMT Best Thesis Award for a PhD or equivalent thesis on a topic related to machine translation
The 16th Machine Translation Summit, organized by the Asia-Pacific Association for Machine Translation (AAMT), will be held at Nagoya University, Japan, in September 18-22 2017.
The 2017 EAMT conference will be held in Prague, Czech Republic, on May 28 – 31
Submission deadline for proposals: October 15, 2016, 23:59 CESTOlder news
EAMT Corporate and Institutional Members
LT³ - Language and translation technology team
Group Website http://research.flw.ugent.be/lt3
Who are we?
LT3 is a research group at Ghent University's Department of Translation, Interpreting and Communication. LT3 conducts fundamental and applied research in the domain of language and translation technology and has extensive expertise in the use of machine learning for the lexico-syntactic and semantic modeling of text (e.g. part-of-speech tagging, anaphora resolution, word sense disambiguation and named entity recognition). LT3 is currently very active in the following areas:
- Translation technology: Translation technology has become an integral part of the translation process, and is one of the more recent additions to the LT3's research agenda. Current topics of interest are the comparison of different methods of translation (human vs. post-editing, human vs. CAT), translation quality assessment, and confidence estimation for machine translation.
- Terminology: Terminology management is crucial both for accurate translation and for intelligent search applications. LT3 has developed a terminology extraction tool that automatically extracts term lists from monolingual and bilingual corpora. Ongoing research projects focus on the automatic detection of synonyms and hyperonyms and terminology extraction from comparable corpora.
- Sentiment analysis and subjectivity detection: The actual meaning of a text goes far beyond the word level. LT3 is currently developing methodologies for sentiment analysis and subjectivity detection through the deep semantic analysis of text and deeply annotated corpora. Envisioned applications are the automatic detection of cyberbullying, suicide detection, opinion mining, personalized advertising, and the detection of subjectivity in annual reports.
Why did we join the EAMT?
LT3 has a track record in machine(-aided) translation and the group participates in a wide range of internationally and nationally funded, and industrial projects. See http://research.flw.ugent.be/lt3 for a list of recent and on-going projects.
LT3 is embedded in Ghent University's Department of Translation, Interpreting and Communication, Flanders' largest course in the field of applied language studies. The department has to date conferred about 4,300 licentiate degrees in translation, interpreting and — since 2004 — MAs of Translation, MAs of Interpreting and MAs of Multilingual Communication.
A variety of courses in translation technology are offered in the curricula at bachelor's, master's and postgraduate level:
- Introduction to Translation Technology
- Terminology and Translation Technology
- Audiovisual Translation
- Audiovisual Language Techniques
- Machine Translation and Post-editing