LIF-CNRS, UMR 7279
Case 901 - 163 Avenue de Luminy
F-13288 MARSEILLE / FRANCE
|Μουρέσι (Pelion), 2017||
'If you talk to a man in a language he understands,
that goes to his head.
If you talk to him in his language, that goes to his heart.' (Nelson Mandela)
I started my research career with the French National Research Centre (CNRS) at LIMSI, an A.I. lab close to Paris.
2006, I moved to the south of France (Marseille) to join the NLP group of LIF (Aix-Marseille Université).
Currently I am emeritus research director at CNRS and Honorary Professor of the Research Institute of Information and Language Processing (RIILP), university of Wolverhampton, UK (1).
Having learned languages under various circumstances, and having observed language acquisition in different contexts, I was intrigued by the fact that most people succeed so well in a natural setting, while they often miserably fail in school. In order to get a better understanding of the causes of this problem, I started to look at language learning from a psycholinguistic and computational linguistic (simulation) perspective.
My Ph.D dissertation was devoted to speaking, a skill that must be learned. Yet, learning to speak and producing language in real time are two daunting tasks. One must not only acquire a huge amount of knowledge (vocabulary, grammar), but also be able to accomplish rapidly and quasi simultaneously the following tasks: message planning, formulation, and articulation. What makes this process even more demanding is the fact that the needed operations must be carried out under sever time and space constraints. Speaking is fast and short-term memory is limited.
Teaching the skills of communication (speaking and writing) is one of the missions of school. Alas, schools don't always succeed very well, and there are various reasons for this. Schools tend to emphasize rules and mechanical repetition, leaving aside the need to integrate rules into a process allowing the stepwise transformation of a conceptual input (message) into its corresponding form (sentence). In sum, they do not show how to convert 'declarative knowledge' (principles, rules) into 'procedural knowledge' (the way of using rules). Hence students may know a lot about language without necessarily knowing the language. Not having acquired the necessary operations (process), they don't know how to convert some input (message) into the corresponding output (sentence). It is also noteworthy that what has been learned (product) does not always correspond to what has been taught, an intuition that was clearly confirmed by the eye track data collected during my Ph.D ("From knowing-what to knowing-how: strategies in language production", Paris, 1980). The data also confirmed that certain methods are inadequate, making learning unnecessarily hard, for not saying impossible. Yet schools are meant to support learning rather than to prevent students from doing so.
Realizing all these facts, I felt that we needed to change our perspective, and, studying language production from a psychological point of view and trying to emulate the process by computer seemed to be a step in the right direction. Here are some of the questions I've asked myself then: (1) When do we process what? (2) What are the inputs and outputs? (3) What are the specific operations and constraints?
Speaking and writing are resource-intensive processes whose success depends not only on knowledge, but also on our momentary ability or skill to access and use it (synthesis). Yet these three conditions are not always met. Hence, our success of producing language lies somewhere in between two extremes : full access to the needed resources, or more or less limited access, yielding sub-optimal performance revealed by gaps, errors, disfluencies, etc.
This being so it makes sense to create authoring aids, i.e. assistive technologies (1, 2, 3, 4, 5), both for supporting the mother tongue or a foreign language. One may even wonder if this is not (also) one of the missions of computational linguistics. Actually, there are good reasons to believe that one should widen the scope and take better into account the human factor (needs and constraints of the human language processor), to build then the adequate tools (Interactive NLP, Human-Centered Computational Language Processing). However, to do so and to get these tools used in real world (desktop, class room), true interdisciplinary work is needed, not only discretely, for not saying 'shamefully', in the backyard, but also more deliberately and clearly visible, at the centre-stage. For additional information concerning the mindset of my approach, see 'Interactive Natural Language Generation' (INLG) here below.
My research interests lie in communication, cognitive science and language production or language generation by and large. Starting from user needs and empirical findings (psycholinguistics, neurosciences) I try to build tools helping people to acquire the skill of speaking or writing in a foreign language and in their mother tongue. My current research deals with the following four topics:
Here is a summary of my research expressed in a few words, or simply by a wordle.
1° Electronic dictionaries and the mental lexicon
CogALex (Cognitive Aspects of the Lexicon), workshop series co-located with COLING :
2016 (cfps : workshop, shared task), Osaka, Japan
2014 (cfps : workshop, shared task),
2012, 2010, 2008 and 2004, a forerunner.
1.2 ICCS (International Conference on Cognitive Science), Beijing, 2010.
1.3 RLTLN (Lexical graphs and NLP), TALN workshop, Marseille, 2014.
2° Natural Language Processing and Cognitive Science (NLPCS)
NLPCS-2013: to access the proceedings, talks and tutorials of this workshop, click here.
Prior events : 2012, 2011, 2010, 2009, 2008, 2007.
3° European Workshop on Natural Language Generation (1995, 1993, 1991, 1989).
4° Tools for AuthoringAids (cfp and proceedings), LREC, Marrakech, 2008.
1° Some thoughts concerning the future of the discipline
1.1RING panel : debate with Eduard Hovy (slides), COLING, 2010, Beijing.
1.2'AI + NLP' : abstract + slides (in french), Paris, 2012.
2° Other topics
Types and uses of semantic networks : genetic, practical and psycholinguistic aspects.
Semantic networks: construction and usage (slides), Imera (Marseille, France)
'Errare humanum est'. Refusing to 'appreciate' this fact could be a big mistake !
ERRARE (Sinaia, Romania).
3° Electronic dictionaries and the mental lexicon
3.1Roget, WordNet and beyond. RANLP-2015, Hissar, Bulgaria.
Needles in a haystack and methods to find them. Can neuroscientists, psychologists and computational linguist help us (to build a tool) to overcome the Tip of the Tongue problem? NetWordS conference : 'Word Knowledge and Word Usage: Representations and Processes in the Mental Lexicon' (Pisa, Italy).
3.3 Wheels for the mind of the language producer: microscopes, macroscopes, semantic maps and a good compass. LREC, Malta, 2010.
3.4 The mental lexicon, blueprint of the dictionaries of tomorrow: linguistic, computational and psychological aspects of a highly valuable resource. ESSLLI, Toulouse, 2009.
3.5 How to help authors to overcome the Tip-Of-the-Tongue problem? Lexical graphs, associative networks, and some of their inherent problems. Toulouse (abstract, slides).
3.6Do you (still) love me? A crash course on telling and recognizing lies. Eurolan-2007, Iași, Romania (abstract, slides).
3.7If all roads lead to Rome, they are not all alike. BLRI (Brain & Language Research Institute), Marseille, 2012 (abstract, in French).
Here is a list of my publications, and here are the links to a book on lexical resources (Gala, N. & Zock, M. (Eds). Ressources Lexicales, John Benjamins, Amsterdam), as well as to some special issues devoted to 'Cognition and the Lexicon' (2015 and 2011). For the respective introductions see here (2015, 2011).
List of Natural Language Generators. For a more recent version see here.
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