Advances in Data Science and AI: Aline Villavicencio

This will be a hybrid event, taking place at The University of Manchester and online.

Contextualised word representation models have been successfully used for capturing distinct (and very specific) word usages, and therefore could provide an attractive alternative for accurately determining meaning in language. However, these models still face a serious challenge when dealing with non-literal language, like that involved in Multiword Expressions (MWEs) such as idioms (make ends meet), light verb constructions (give a sigh), verb particle constructions (shake up) and noun compounds (loan shark). MWEs are an integral part of the mental lexicon of native speakers often used to express complex ideas in a simple and conventionalised way accepted by a given linguistic community. Although they may display a wealth of idiosyncrasies, from lexical, syntactic and semantic to statistical, that represents a real challenge for current NLP techniques, their accurate integration has the potential for improving the precision, naturalness and fluency of downstream tasks like machine translation. In this talk, I will present an overview of how advances in word representations have made an impact for the identification and modelling of idiomaticity and MWEs. I will concentrate on what models seem to incorporate of idiomaticity, as idiomatic interpretation may require knowledge that goes beyond what can be gathered from the individual words of an expression (e.g. “dark horse” as an unknown candidate who unexpectedly succeeds).

Bio: Aline Villavicencio is the Chair in Natural Language Processing at the Department of Computer Science, University of Sheffield (UK) and affiliated to the Institute of Informatics, Federal University of Rio Grande do Sul (Brazil). She received her PhD from the University of Cambridge (UK) in 2001, and held postdoc positions at the University of Cambridge and University of Essex (UK). She was a Visiting Scholar at the Massachusetts Institute of Technology (USA, 2011-2012 and 2014-2015), at the École Normale Supé¬rieure (France, 2014), an Erasmus-Mundus Visting Scholar at Saarland University (Germany in 2012/2013) and at the University of Bath (UK, 2006-2009). She held a Research Fellowship from the Brazilian National Council for Scientific and Technological Development (Brazil, 2009-2017). She is a member of the editorial board of Computational Linguistics, TACL and of JNLE. She was the PC Co-Chair of the 60th Meeting of the Association for Computational Linguistics (ACL 2022), and was the PC chair of CoNLL-2019, Senior Area Chair for ACL-2020 and ACL-2019 among others and General co-chair for the 2018 International Conference on Computational Processing of Portuguese. She is also a member of the NAACL board, SIGLEX board and of the program committees of various *ACL and AI conferences, and has co-chaired several *ACL workshops on Cognitive Aspects of Computational Language Acquisition and on Multiword Expressions. Her research interests include lexical semantics, multilinguality, multiword expressions and cognitively motivated NLP, and has co-edited special issues and books dedicated to these topics.

This event has been organised by the Institute for data Science and AI.

IDSAI is one of The University of Manchester's Digital Futures network themes.

Event Venue & Nearby Stays

A116, Samuel Alexander Building, Oxford Road, Manchester, United Kingdom