Taaltechnologie ontrafeld

Veronique Hoste is Senior Full Professor of Computational Linguistics at the Faculty of Arts and Philisophy at Ghent University. She is department head of the Department of Translation, Interpreting and Communication and director of the LT3 language and translation team at the same department. She holds a PhD in computational linguistics from the University of Antwerp (Belgium) on "Optimization issues in machine learning of coreference resolution" (2005).

Natural language processing in the last decades has drastically shifted from a discipline in which linguistic rules were handcrafted by experts to a vibrant discipline heavily dominated by machine learning and more recently, end-to-end neural approaches. Véronique has a strong track record in combining linguistic expertise with machine learning of natural language, seeking to automatically model natural language up to the level of semantics and discourse in a wide range of applications, such as cyberbully detection or sentiment and emotion analysis.

Cynthia Van Hee is a lecturer and postdoctoral researcher at Ghent University, affiliated with the LT³ Language and Translation Technology Team. Her work as a postdoc centers on computational linguistics and machine learning, with a focus on sentiment analysis, irony detection, and linguistic preprocessing. She teaches several courses related to language technology, including Data Processing with Python and Natural Language Processing, as part of the Applied Linguistics programme and the Computer-Assisted Language Technology postgraduate.

Orphée is assistant professor of language technology for educational applications. She is mainly interested in how natural language processing techniques can aid computer-assisted language learning. She has great expertise in deep semantic processing, readability prediction and text mining of subjective user-generated content using machine learning techniques.

Orphée is teaching two courses on digital communication, is lecturer-in-charge of the course Computer-Assisted Language Learning and always eager to supervise Bachelor and Master students to help them take their first steps into the wonderful world of Natural Language Processing.

Expertise: Taaltechnologie, machinelearning, computerondersteund taalleren

Els Lefever is hoofddocent bij de vakgroep Vertalen, Tolken en Communicatie, en is verbonden aan de onderzoeksgroep LT3 (Language and Translation Technology Team) en het Ghent Center for Digital Humanties. Els startte haar carrière als computationeel taalkundige in de R&D afdeling van Lernout & Hauspie Speech products, en behaalde haar doctoraat in de computerwetenschappen aan de UGent in 2012. Haar onderzoek richt zich op machine learning van natuurlijke talen en meertalige NLP, met een speciale focus op computationele semantiek, sentimentanalyse, automatische terminologie-extractie en digital humanities. Ze begeleidt doctoraatsonderzoek naar het modelleren van talen met weinig data, argumentatie in politieke social media berichten, NLP methodes voor Byzantijns Grieks en spijkerschrift, en het automatisch linken van lekentaal en professionele taal voor medische teksten. Ze doceert vakken over terminologie en vertaaltechnologie, digitale tekstanalyse, lokalisatie en digital humanities.

Expertise: Natural Language Processing, Machine Learning

Lieve Macken is Associate Professor at the Department of Translation, Interpreting and Communication of Ghent University with 28 years of experience in language technology. She started her career at the Center for Computational Linguistics of the University of Leuven, developing a Simplified English Grammar Checker and Corrector (SECC), which was used as a front-end for machine translation systems helping to improve translation quality and reduce post-editing work by simplifying the input.

She is coordinator of the postgraduate program Computer-Assisted Language Mediation, co-coordinator of the European Master's in Technology for Translation and Interpreting (EM-TTI). She teaches Computer-Assisted Translation, Machine Translation, and Dissertation (parts I and II).

Arda Tezcan, with a background in mathematics and artificial intelligence, earned his Ph.D. in translation studies. He is an active member of the Language and Translation Technology Team (LT3), focusing his research on areas such as natural language processing, machine translation, and human-machine interaction within translation studies. He also teaches courses on natural language processing, programming, and translation technology.

A. Seza Doğruöz is a Tenured Faculty/Professor at Ghent University (Language Technologies for Multilingual and Mixed Low Resource Languages, Computational Sociolinguistics & Open-Domain Dialogue Systems).

In her research, she analyzes the diversity in social and linguistic aspectsof human-human and human-machine interactions (e.g., open-domain dialogue systems, HRI) across media (e.g. face-to-face, digital environments) through both qualitative and computational methods of analyses. She has worked extensively on multilingualism & linguistic diversity around the world (e.g., Europe, Asia, South America, Africa) from a dynamic point of view including variation and change as major components for communication between humans and authored interdisciplinary research output (see below).

Joke Daems is assistant professor human-computer interaction in empirical translation & interpreting studies at Ghent University. They conduct research as a member of EQTIS (Empirical and Quantitative Translation and Interpreting Studies) and collaborate closely with the Language and Translation Technology Team (LT³). They obtained a PhD in Translation Studies at Ghent University in 2016, working on identifying the differences between human translation and post-editing for students and professional translators. This work was awarded the CIUTI PhD Award in 2017. Their research interests include (machine) translation, post-editing, translatability, human-computer interaction, and literary translation and style. Future work will focus on the potential of adaptive MT for gender-inclusive language and technology for L2 translation.

Joke teaches courses on terminology and translation technology, machine translation and post-editing, and technical writing. They are happy to supervise dissertations in the broader field of human-computer interaction within translation and interpreting studies.