Albert Rilliard – Comparaison interculturelle de la perception et de la production d’expressions attitudinales

Albert Rilliard
Chercheur au Laboratoire d’Informatique pour la Mécanique et les Sciences de l’Ingénieur
CNRS, Paris
Le mercredi 11 décembre 2013 à 12h30
Salle DS-1950



La prosodie, parmi de multiples fonctions, permet au locuteur d’exprimer son attitude envers son discours ou envers son interlocuteur.
De telles expressions participent à la gestion de l’interaction parlée en améliorant l’efficacité des actes de langage (expressions de doute ou de surprise), ou en aidant à gérer les rapports interpersonnels de manière moins explicite qu’en utilisant le lexique (expressions d’autorité, de mépris ou de politesse).

Ces attitudes suivent des codes – icônes universelles (cf. le « frequency code » de J. Ohala) ou spécifiques à une langue et une culture (l’expression du concept japonais de « kyoshuku »).

Comment ces attitudes sont perçues, en ou hors contexte, par des locuteurs d’autres cultures ? Les choix d’encodage de ces expressions sont-ils similaires dans différentes langues, et sont-ils compatibles ?

Ces questions seront abordées au travers des résultats d’une expérience de perception interculturelle mélangeant codes prosodiques, visuels et descriptions conceptuelles, puis par la description de l’analyse acoustique d’enregistrements collectés auprès de locuteurs de différentes origines.


Jim Hendler – Why Watson Won ?

Jim Hendler
Tetherless World Professor of Computer, Web and Cognitive Sciences
Director, Rensselaer Institute for Data Exploration and Applications
Rennselaer Polytechnic Institute

Le mercredi 20 novembre 2013 à 9h30, Salle PK-1140

Why Watson Won ?


In 2011, the IBM computer program Watson beat the world’s best players at the quiz show Jeopardy! by a considerable margin. In the time since, Watson has been being developed to handle medical diagnosis and other problems using the same general question-answering framework. The capabilities of Watson exceeded the expectations of many in the AI and cognitive science communities, and the performance levels it shows in other tasks continues to be an exciting advance in human language technology.

Earlier this year, Rensselaer Polytechnic Institute became the first academic institution to receive the Watson software. We have been exploring how Watson’s DeepQA architecture can be used in tasks ranging from being an “open data advisor” to answering trivia questions about the Star Wars universe. We have also been trying to gain insight into why it is that this particular architectural approach was able to do so well in what has been seen as a task requiring human problem solving. In this talk, we discuss this latter question. We explain the process used by Watson in playing Jeopardy!, focusing on the question-answering pipeline and the various algorithms used therein. In particular, I will explore how the pipeline compares to some other cognitive theories and whether there are insights we can gain from this approach with respect to human quiz show performance.


James Hendler is the Director of the Institute for Data Exploration and Applications and the Tetherless World Professor of Computer, Web and Cognitive Sciences at RPI. He also serves as a Director of the UK’s charitable Web Science Trust. Hendler has authored over 200 technical papers in the areas of Semantic Web, artificial intelligence, agent-based computing and high performance processing. One of the originators of the “Semantic Web,” Hendler was the recipient of a 1995 Fulbright Foundation Fellowship, is a former member of the US Air Force Science Advisory Board, and is a Fellow of the American Association for Artificial Intelligence, the British Computer Society, the IEEE and the AAAS. He is also the former Chief Scientist of the Information Systems Office at the US Defense Advanced Research Projects Agency (DARPA) and was awarded a US Air Force Exceptional Civilian Service Medal in 2002. He is also the first computer scientist to serve on the Board of Reviewing editors for Science. In 2010, Hendler was named one of the 20 most innovative professors in America by Playboy magazine and was selected as an “Internet Web Expert” by the US government. In 2012, he was one of the inaugural recipients of the Strata Conference “Big Data” awards for his work on large-scale open government data, and he is a columnist and associate editor of the Big Data journal. In 2013, he was appointed Open Data Advisor to New York State by Governor Cuomo.


Michael Ullman – Do we learn language in the same brain systems that rats use to learn a maze? Evidence from a multidisciplinary investigation of first and second language

Le vendredi 15 novembre 2013 à 15h00, Salle DS-3470


Michael Ullman
Departments of Neuroscience, Linguistics, Psychology and Neurology
Georgetown University, Washington, DC

Increasing evidence suggests that language learning and use crucially depend on two long-term memory systems in the brain, declarative memory and procedural memory. Because the behavioral, anatomical, physiological, cellular and genetic correlates of these two systems are quite well-studied in animals and humans, they lead to specific predictions about language that would not likely be made in the more limited study of language alone. This approach is thus very powerful in being able to generate a wide range of new predictions for language – including for first and second language, individual differences, and a range of language disorders.

I will first give some background on the two memory systems, and then discuss the manner in which language is predicted to depend on them. One of the key concepts is that to some extent the two systems can subserve the same functions (e.g., for navigation, grammar, etc.), and thus they play at least partly redundant roles for these functions. This has a variety of important consequences for normal and disordered language. I will then present multidisciplinary evidence (behavioral, neurological, neuroimaging, electrophysiological) that basic aspects of language do indeed depend on the two memory systems, though in different ways across different unimpaired and impaired populations. I will discuss normal first and second language, individual and group differences (e.g., sex differences), and our work on disorders, focusing on developmental disorders (e.g., Specific Language Impairment, dyslexia, autism, and Tourette syndrome).


Dr. Ullman is Professor in the Department of Neuroscience, with secondary appointments in the Departments of Neurology, Linguistics and Psychology, at Georgetown University. He is Director of the Brain and Language Laboratory and the Georgetown EEG/ERP Lab. His research examines the brain bases of first and second language, how language and memory are affected in various disorders (e.g., autism, Specific Language Impairment, aphasia, Alzheimer’s, Parkinson’s and Huntington’s diseases), and how factors such as sex, handedness, and genetic variability affect the brain bases of language and memory.

Sydney Lamb – Unlocking the Mind with the Key of Language: Relational Networks as a Bridge from Linguistics to Neuroscience

Le vendredi 4 octobre 2013 à 15h00, Salle DS-1950


Sydney Lamb
Rice University

If cortical structures for language are like those for other high-level skills, then if we figure out language, we also have the answer to how the cortex manages other kinds of mental processing. My claim is that the relational network theory of language provides also a general theory of cortical operation and that we can therefore now understand the essentials of higher-level human information processing more generally. This principle is illustrated by an explanatory account of unconscious priming effects on behavior as studied in cognitive psychology.


Sydney Lamb received his Ph.D. in Linguistics fro the University of California, Berkeley, and has taught at UC Berkeley, Yale University, and (for thirty years) at Rice University, where he is now Professor Emeritus of Linguistics and Cognitive Science. Known as the chief originator of Stratificational Linguistics and its theory of relational networks. He is the author of Pathways of the Brain (1999) and Language and Reality (2004).

Jesse Prinz – Consciousness is Attention

Le vendredi 3 mai 2013 à 15h00, Salle DS-1950

Jesse Prinz
CUNY Graduate Center

Recent work in cognitive neuroscience and psychology established a close relationship between attention and consciousness. There is evidence that consciousness comes and goes with attention. This suggests that attention is the basis of consciousness, and that the neural correlates of attention are the neural correlates of consciousness. There is, however, also a growing body of research that tries to establish a double dissociation between attention and consciousness. In this lecture, evidence for the link between attention and consciousness is reviewed, and alternative interpretations of alleged dissociations are offered.


Robert DeKeyser – The ‘critical period’ debate: past, present, and future

Le vendredi  12 avril 2013 à 15h00, Salle DS-3470

Robert DeKeyser
University of Maryland 

For half a century now, age effects in second language learning have been the subject of intense debate. After a brief overview of how the focus of the debate has shifted repeatedly over the decades and a short state of the art, I will focus on the issue of explanatory adequacy and on various methodological issues from sampling to statistical analysis. Finally, I will suggest priorities for future research on this topic, including the potential contribution of under-researched populations (the hearing-impaired, heritage language learners, immigrants with little formaleducation, and learners of marginalized languages).

Bertram Gawronski – Contextualized Representation and Automatic Evaluation

22 mars à 15h00 au DS-1950. 

Bertram Gawronski, The University of Western Ontario

Automatic evaluative responses play a central role in many areas of psychology. Counter to views that such responses are relatively rigid and inflexible, a large body of research has shown that they are highly context-sensitive. One issue that is less well understood, however, is when and why automatic evaluations are context-dependent or context-independent. The current talk presents a representational account that specifies when and how context information is included in the evaluative representation of an object, thereby modulating automatic evaluative responses to that object. Drawing on the concepts of occasion setting and renewal in animal learning, the account implies precise predictions about the contextual conditions under which automatic evaluations reflect (a) initially acquired information; (b) subsequently acquired, counterattitudinal information; or (c) a mixture of both. The talk includes findings from a set of studies that tested these predictions and several hypotheses about the particular way in which contextual information is stored in memory. Implications for various applications (e.g., treatment of dysfunctional or undesired automatic evaluative responses) will be discussed.

Bertram Gawronski is Professor of Psychology and Canada Research Chair in Social Psychology at The University of Western Ontario (Canada). He completed his M.A. in Philosophy in 1998 at the Free University of Berlin (Germany) and his Ph.D. in Psychology in 2001 at Humboldt University Berlin (Germany). Before he accepted his current position at The University of Western Ontario, he was a postdoctoral fellow at the University of Würzburg (Germany) and Northwestern University (USA). His research aims at understanding the mechanisms underlying spontaneous and deliberate evaluations, with a particular focus on the role of associative and propositional processes. He served as Associate Editor of the Journal of Personality and Social Psychology and his work has been recognized with multiple awards, including the Theoretical Innovation Prize from the Society for Personality and Social Psychology, the Early Career Award from the International Social Cognition Network, and the Early Researcher Award from the Ministry of Research and Innovation of Ontario.

Institut des sciences cognitives

Fondé en 2003, l'Institut des Sciences Cognitives de l'UQAM vise à favoriser la recherche et le développement de compétences dans le domaine des sciences cognitives, à en partager les connaissances, à faciliter les échanges interdisciplinaires et à animer la communauté locale.


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