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1. EARN Fairness: Explaining, Asking, Reviewing and Negotiating Artificial Intelligence Fairness Metrics Among Stakeholders

Author

Luo, Lin, Nakao, Yuri, Chollet, Mathieu, Inakoshi, Hiroya, and Stumpf, Simone

Subjects
Computer Science - Artificial Intelligence, Computer Science - Computers and Society, Computer Science - Human-Computer Interaction
Abstract

Numerous fairness metrics have been proposed and employed by artificial intelligence (AI) experts to quantitatively measure bias and define fairness in AI models. Recognizing the need to accommodate stakeholders' diverse fairness understandings, efforts are underway to solicit their input. However, conveying AI fairness metrics to stakeholders without AI expertise, capturing their personal preferences, and seeking a collective consensus remain challenging and underexplored. To bridge this gap, we propose a new framework, EARN Fairness, which facilitates collective metric decisions among stakeholders without requiring AI expertise. The framework features an adaptable interactive system and a stakeholder-centered EARN Fairness process to Explain fairness metrics, Ask stakeholders' personal metric preferences, Review metrics collectively, and Negotiate a consensus on metric selection. To gather empirical results, we applied the framework to a credit rating scenario and conducted a user study involving 18 decision subjects without AI knowledge. We identify their personal metric preferences and their acceptable level of unfairness in individual sessions. Subsequently, we uncovered how they reached metric consensus in team sessions. Our work shows that the EARN Fairness framework enables stakeholders to express personal preferences and reach consensus, providing practical guidance for implementing human-centered AI fairness in high-risk contexts. Through this approach, we aim to harmonize fairness expectations of diverse stakeholders, fostering more equitable and inclusive AI fairness.

Published
2024

3. Using Multimodal Data to Predict Surgeon Situation Awareness

Author

Lechappe, Aurelien, Chollet, Mathieu, Rigaud, Jerome, Cao, Caroline G. L., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Black, Nancy L., editor, Neumann, W. Patrick, editor, and Noy, Ian, editor

Published
2022
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5. Affect-LM: A Neural Language Model for Customizable Affective Text Generation

Author

Ghosh, Sayan, Chollet, Mathieu, Laksana, Eugene, Morency, Louis-Philippe, and Scherer, Stefan

Subjects
Computer Science - Computation and Language
Abstract

Human verbal communication includes affective messages which are conveyed through use of emotionally colored words. There has been a lot of research in this direction but the problem of integrating state-of-the-art neural language models with affective information remains an area ripe for exploration. In this paper, we propose an extension to an LSTM (Long Short-Term Memory) language model for generating conversational text, conditioned on affect categories. Our proposed model, Affect-LM enables us to customize the degree of emotional content in generated sentences through an additional design parameter. Perception studies conducted using Amazon Mechanical Turk show that Affect-LM generates naturally looking emotional sentences without sacrificing grammatical correctness. Affect-LM also learns affect-discriminative word representations, and perplexity experiments show that additional affective information in conversational text can improve language model prediction.

Published
2017

9. Expressing social attitudes in virtual agents for social training games

Author

Sabouret, Nicolas, Jones, Hazaël, Ochs, Magalie, Chollet, Mathieu, and Pelachaud, Catherine

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Artificial Intelligence, Computer Science - Computers and Society
Abstract

The use of virtual agents in social coaching has increased rapidly in the last decade. In order to train the user in different situations than can occur in real life, the virtual agent should be able to express different social attitudes. In this paper, we propose a model of social attitudes that enables a virtual agent to reason on the appropriate social attitude to express during the interaction with a user given the course of the interaction, but also the emotions, mood and personality of the agent. Moreover, the model enables the virtual agent to display its social attitude through its non-verbal behaviour. The proposed model has been developed in the context of job interview simulation. The methodology used to develop such a model combined a theoretical and an empirical approach. Indeed, the model is based both on the literature in Human and Social Sciences on social attitudes but also on the analysis of an audiovisual corpus of job interviews and on post-hoc interviews with the recruiters on their expressed attitudes during the job interview.

Published
2014

13. Racing Heart and Sweaty Palms : What Influences Users’ Self-Assessments and Physiological Signals When Interacting with Virtual Audiences?

Author

Chollet, Mathieu, Massachi, Talie, Scherer, Stefan, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Beskow, Jonas, editor, Peters, Christopher, editor, Castellano, Ginevra, editor, O'Sullivan, Carol, editor, Leite, Iolanda, editor, and Kopp, Stefan, editor

Published
2017
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15. An Architecture for Biologically Grounded Real-Time Reflexive Behavior

Author

Bernardet, Ulysses, Chollet, Mathieu, DiPaola, Steve, Scherer, Stefan, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Traum, David, editor, Swartout, William, editor, Khooshabeh, Peter, editor, Kopp, Stefan, editor, Scherer, Stefan, editor, and Leuski, Anton, editor

Published
2016
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16. Manipulating the Perception of Virtual Audiences Using Crowdsourced Behaviors

Author

Chollet, Mathieu, Chandrashekhar, Nithin, Shapiro, Ari, Morency, Louis-Philippe, Scherer, Stefan, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Traum, David, editor, Swartout, William, editor, Khooshabeh, Peter, editor, Kopp, Stefan, editor, Scherer, Stefan, editor, and Leuski, Anton, editor

Published
2016
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17. Towards a Socially Adaptive Virtual Agent

Author

Ben Youssef, Atef, Chollet, Mathieu, Jones, Hazaël, Sabouret, Nicolas, Pelachaud, Catherine, Ochs, Magalie, Goebel, Randy, Series editor, Tanaka, Yuzuru, Series editor, Wahlster, Wolfgang, Series editor, Brinkman, Willem-Paul, editor, Broekens, Joost, editor, and Heylen, Dirk, editor

Published
2015
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18. From Non-verbal Signals Sequence Mining to Bayesian Networks for Interpersonal Attitudes Expression

Author

Chollet, Mathieu, Ochs, Magalie, Pelachaud, Catherine, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, Series editor, Tanaka, Yuzuru, Series editor, Wahlster, Wolfgang, Series editor, Siekmann, Jörg, Series editor, Bickmore, Timothy, editor, Marsella, Stacy, editor, and Sidner, Candace, editor

Published
2014
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20. Computational Model of Film Editing for Interactive Storytelling

Author

Lino, Christophe, Chollet, Mathieu, Christie, Marc, Ronfard, Remi, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Si, Mei, editor, Thue, David, editor, André, Elisabeth, editor, Lester, James C., editor, Tanenbaum, Theresa Jean, editor, and Zammitto, Veronica, editor

Published
2011
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21. Study 8: Cross Validation Final Questionnaire Set

Author

Fitrianie, Siska, Brinkman, Willem-Paul, Bruijnes, Merijn, Abdulrahman, Amal, Li, Fengxiang, Baraka, Kim, van den Berghe, Rianne, Bernardet, Ulysses, Bosse, Tibor, Brazier, Frances, Browne, Jacob, Burger, Franziska, Chollet, Mathieu, Clark, Leigh, Cowan, Benjamin, Daher, Salam, Ding, Ding, Foerster, Frank, Gilmartin, Emer, Jonker, Catholijn, de Haas, Mirjam, Hashemian, Mojgan, Heyselaar, Evelien, Kim, Kangsoo, Koelle, Marion, Kuhnert, Barbara, Lindner, Felix, Linssen, Jeroen, Lucas, Gale, Lun, Wang, Martens, Chris, Molnár, Bálint, Norouzi, Nahal, Bierbach, Catharine, Pelachaud, Catherine, Richards, Deborah, Silvervarg, Annika, Tielman, Myrthe, Yalçın, Özge, Rajanen, Dorina, Lisetti, Christine, Rodriguez Lera, Francisco, Kunold, Laura, Morgan, Jay, Wächter, Laura, Ham, Jaap, Yasir, Muhammad, Kalvas, František, Barakova, Emilia, akalin, neziha, GHAZALI, AIMI, Alonso, Victoria, Kocaballi, A., Parthemore, Joel, Guerrero, Esteban, Neff, Michael, Torre, Ilaria, Beun, Robbert, Magyar, Gergely, Belhassein, Kathleen, hall, lynne, Kristoffersson, Annica, Olafsson, Stefan, de Vries, Roelof, van Waterschoot, Jelte, Zaga, Zaga, Cristina, Cristina, Charrier, Laurianne, Yacoubi, Alya, Roper, Abi, abdulrahman, amal, Zalake, Mohan, Carnell, Stephanie, Hindriks, Koen, Roohi, Samad, Ligthart, Mike, Sirocki, Jeffrey, Bönsch, Andrea, Howcroft, David, Ochs, Hudlicka, Eva, Gnewuch, Ulrich, Gunson, Nancie, Jingar, Monika, Hartmann, Tilo, van Miltenburg, Emiel, Cox, Samuel, Richards, Byronie, Kucherenko, Taras, Jonell, Patrik, Vilhjálmsson, Hannes, Wolfert, Pieter, Ranjbartabar, Hedieh, Wang, Isaac, Kun, Peter, Wicke, Philipp, HE, Yuan, Simoens, Pieter, Biancardi, Beatrice, Zibrek, Katja, McCoy, Joshua, Tsfasman, Maria, Vossen, Piek, Ribeiro, Tiago, Krause, Lea, Beinema, Tessa, and Curtis, Cassidy

Subjects
Virtual Agent, User Study, Artificial Intelligence and Robotics, Computer Sciences, Questionnaire, Graphics and Human Computer Interfaces, Physical Sciences and Mathematics, Robotics, Evaluation Instruments, Intelligent Agent
Abstract

In this study, we determine the generalization performance of the long and short questionnaire version (i.e. cross validation: fit model on data set from a new set of ASAs). It involves crowd workers on an online platform. They will be asked to use the questionnaire instrument to rate an interaction between an agent and a human user, which is displayed in a 30 second video clip.

Published
2022
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22. Study 1: Defining Categories

Author

Fitrianie, Siska, Baraka, Kim, van den Berghe, Rianne, Bernardet, Ulysses, Bosse, Tibor, Brazier, Frances, Brinkman, Willem-Paul, Browne, Jacob, Bruijnes, Merijn, Burger, Franziska, Chollet, Mathieu, Clark, Leigh, Cowan, Benjamin, Daher, Salam, Ding, Ding, Foerster, Frank, Gilmartin, Emer, Jonker, Catholijn, de Haas, Mirjam, Hashemian, Mojgan, Heyselaar, Evelien, Kim, Kangsoo, Koelle, Marion, Kuhnert, Barbara, Lindner, Felix, Linssen, Jeroen, Lucas, Gale, Lun, Wang, Martens, Chris, Molnár, Bálint, Norouzi, Nahal, Bierbach, Catharine, Pelachaud, Catherine, Richards, Deborah, Silvervarg, Annika, Tielman, Myrthe, Yalçın, Özge, Rajanen, Dorina, Lisetti, Christine, Rodriguez Lera, Francisco, Kunold, Laura, Morgan, Jay, Wächter, Laura, Ham, Jaap, Yasir, Muhammad, Kalvas, František, Barakova, Emilia, akalin, neziha, GHAZALI, AIMI, Harth, Jonathan, Casals, Arthur, Alonso, Victoria, Kocaballi, A., Parthemore, Joel, Guerrero, Esteban, Neff, Michael, Torre, Ilaria, Beun, Robbert, Magyar, Gergely, Belhassein, Kathleen, hall, lynne, Kristoffersson, Annica, and Olafsson, Stefan

Subjects
Virtual Agent, Expert review, User Study, Questionnaire, Robotics, Evaluation Instruments, Questionnaire's categories, Intelligent Agent
Abstract

A study that involves experts to group existing constructs into a set of categories (based on Evaluation Instrument Model 4). This study aims to investigate whether or not we have covered all aspects that people (based on the previous research) aim to measure in evaluating human interaction with a social agent.

Published
2022
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23. Study 6: Analysing Reliability of Questionnaire Items

Author

Fitrianie, Siska, Brinkman, Willem-Paul, Bruijnes, Merijn, Baraka, Kim, van den Berghe, Rianne, Bernardet, Ulysses, Bosse, Tibor, Brazier, Frances, Browne, Jacob, Burger, Franziska, Chollet, Mathieu, Clark, Leigh, Cowan, Benjamin, Daher, Salam, Ding, Ding, Foerster, Frank, Gilmartin, Emer, Jonker, Catholijn, de Haas, Mirjam, Hashemian, Mojgan, Heyselaar, Evelien, Kim, Kangsoo, Koelle, Marion, Kuhnert, Barbara, Lindner, Felix, Linssen, Jeroen, Lucas, Gale, Lun, Wang, Martens, Chris, Molnár, Bálint, Norouzi, Nahal, Bierbach, Catharine, Pelachaud, Catherine, Richards, Deborah, Silvervarg, Annika, Tielman, Myrthe, Yalçın, Özge, Rajanen, Dorina, Lisetti, Christine, Rodriguez Lera, Francisco, Kunold, Laura, Morgan, Jay, Wächter, Laura, Ham, Jaap, Yasir, Muhammad, Kalvas, František, Barakova, Emilia, akalin, neziha, GHAZALI, AIMI, Alonso, Victoria, Kocaballi, A., Parthemore, Joel, Guerrero, Esteban, Neff, Michael, Torre, Ilaria, Beun, Robbert, Magyar, Gergely, Belhassein, Kathleen, hall, lynne, Kristoffersson, Annica, Olafsson, Stefan, de Vries, Roelof, van Waterschoot, Jelte, Zaga, Zaga, Cristina, Cristina, Charrier, Laurianne, Yacoubi, Alya, Roper, Abi, abdulrahman, amal, Zalake, Mohan, Nijssen, Sari, Carnell, Stephanie, Hindriks, Koen, Roohi, Samad, Ligthart, Mike, Sirocki, Jeffrey, Bönsch, Andrea, Howcroft, David, Ochs, Hudlicka, Eva, Gnewuch, Ulrich, Gunson, Nancie, Jingar, Monika, Hartmann, Tilo, Li, Fengxiang, van Miltenburg, Emiel, Cox, Samuel, Richards, Byronie, Kucherenko, Taras, Jonell, Patrik, Vilhjálmsson, Hannes, Wolfert, Pieter, Ranjbartabar, Hedieh, Wang, Isaac, Kun, Peter, and Wicke, Philipp

Subjects
Virtual Agent, User Study, Artificial Intelligence and Robotics, Computer Sciences, Questionnaire, ComputerApplications_MISCELLANEOUS, Graphics and Human Computer Interfaces, Physical Sciences and Mathematics, Robotics, Evaluation Instruments, Intelligent Agent
Abstract

This research is the first study into the validation of the questionnaire instrument for evaluating human interaction with an artificial social agent. It involves crowd workers on an online crowdsourcing platform. They will be asked to use the questionnaire instrument to rate an interaction between an agent and a human user, which is displayed in a 30 second video clip. The result of this study will be analysed and used to examine the reliability of individual questionnaire items in the questionnaire instrument.

Published
2022
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24. Study 7: Confirmatory Factor Analysis

Author

Fitrianie, Siska, Brinkman, Willem-Paul, Bruijnes, Merijn, Baraka, Kim, van den Berghe, Rianne, Bernardet, Ulysses, Bosse, Tibor, Brazier, Frances, Browne, Jacob, Burger, Franziska, Chollet, Mathieu, Clark, Leigh, Cowan, Benjamin, Daher, Salam, Ding, Ding, Foerster, Frank, Gilmartin, Emer, Jonker, Catholijn, de Haas, Mirjam, Hashemian, Mojgan, Heyselaar, Evelien, Kim, Kangsoo, Koelle, Marion, Kuhnert, Barbara, Lindner, Felix, Linssen, Jeroen, Lucas, Gale, Lun, Wang, Martens, Chris, Molnár, Bálint, Norouzi, Nahal, Bierbach, Catharine, Pelachaud, Catherine, Richards, Deborah, Silvervarg, Annika, Tielman, Myrthe, Yalçın, Özge, Rajanen, Dorina, Lisetti, Christine, Rodriguez Lera, Francisco, Kunold, Laura, Morgan, Jay, Wächter, Laura, Ham, Jaap, Yasir, Muhammad, Kalvas, František, Barakova, Emilia, akalin, neziha, GHAZALI, AIMI, Alonso, Victoria, Kocaballi, A., Parthemore, Joel, Guerrero, Esteban, Neff, Michael, Torre, Ilaria, Beun, Robbert, Magyar, Gergely, Belhassein, Kathleen, hall, lynne, Kristoffersson, Annica, Olafsson, Stefan, de Vries, Roelof, van Waterschoot, Jelte, Zaga, Zaga, Cristina, Cristina, Charrier, Laurianne, Yacoubi, Alya, Roper, Abi, abdulrahman, amal, Zalake, Mohan, Nijssen, Sari, Carnell, Stephanie, Hindriks, Koen, Roohi, Samad, Ligthart, Mike, Sirocki, Jeffrey, Bönsch, Andrea, Howcroft, David, Ochs, Hudlicka, Eva, Gnewuch, Ulrich, Gunson, Nancie, Jingar, Monika, Hartmann, Tilo, Li, Fengxiang, van Miltenburg, Emiel, Cox, Samuel, Richards, Byronie, Kucherenko, Taras, Jonell, Patrik, Vilhjálmsson, Hannes, Wolfert, Pieter, Wang, Isaac, Ranjbartabar, Hedieh, Kun, Peter, Wicke, Philipp, HE, Yuan, Simoens, Pieter, Biancardi, Beatrice, and Zibrek, Katja

Subjects
Virtual Agent, User Study, Artificial Intelligence and Robotics, Computer Sciences, Questionnaire, ComputerApplications_MISCELLANEOUS, Graphics and Human Computer Interfaces, Physical Sciences and Mathematics, Robotics, Evaluation Instruments, Intelligent Agent
Abstract

This research is the second study into the validation of the questionnaire instrument for evaluating human interaction with an artificial social agent. It involves crowd workers on an online crowdsourcing platform. They will be asked to use the questionnaire instrument to rate an interaction between an agent and a human user, which is displayed in a 30 second video clip. The result of this study will be analysed and used to examine the associations of questionnaire items with the latent constructs, i.e. construct validity.

Published
2022
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25. Study 2: Defining Constructs

Author

Fitrianie, Siska, Brinkman, Willem-Paul, Bruijnes, Merijn, Baraka, Kim, van den Berghe, Rianne, Bernardet, Ulysses, Bosse, Tibor, Brazier, Frances, Browne, Jacob, Ochs, Hudlicka, Eva, Gnewuch, Ulrich, Burger, Franziska, Chollet, Mathieu, Clark, Leigh, Cowan, Benjamin, Daher, Salam, Ding, Ding, Foerster, Frank, Gilmartin, Emer, Jonker, Catholijn, Ligthart, Mike, Sirocki, Jeffrey, Bönsch, Andrea, Howcroft, David, de Haas, Mirjam, Hashemian, Mojgan, Heyselaar, Evelien, Kim, Kangsoo, Koelle, Marion, Kuhnert, Barbara, Lindner, Felix, Linssen, Jeroen, Lucas, Gale, Lun, Wang, Martens, Chris, Molnár, Bálint, Norouzi, Nahal, Bierbach, Catharine, Pelachaud, Catherine, Richards, Deborah, Silvervarg, Annika, Tielman, Myrthe, Yalçın, Özge, Rajanen, Dorina, Lisetti, Christine, Rodriguez Lera, Francisco, Kunold, Laura, Morgan, Jay, Wächter, Laura, Ham, Jaap, Yasir, Muhammad, Kalvas, František, Hindriks, Koen, Roohi, Samad, Charrier, Laurianne, Yacoubi, Alya, Roper, Abi, abdulrahman, amal, Zalake, Mohan, Nijssen, Sari, Carnell, Stephanie, Barakova, Emilia, akalin, neziha, GHAZALI, AIMI, Casals, Arthur, Alonso, Victoria, Kocaballi, A., Parthemore, Joel, Guerrero, Esteban, Neff, Michael, Torre, Ilaria, Beun, Robbert, Magyar, Gergely, Belhassein, Kathleen, hall, lynne, Kristoffersson, Annica, Olafsson, Stefan, de Vries, Roelof, van Waterschoot, Jelte, Zaga, Zaga, Cristina, and Cristina

Subjects
Virtual Agent, User Study, Questionnaire, Robotics, Evaluation Instruments, Intelligent Agent
Abstract

A study that involves experts to organize constructs (within seven categories resulted in the Study 1: Defining Categories) into groups.

Published
2022
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35. Etude de l'influence du comportement d'un public virtuel sur le stress ressenti lors de prises de paroles simulées

Author

Chollet, Mathieu, Massachi, Talie, Scherer, Stefan, Département Automatique, Productique et Informatique (IMT Atlantique - DAPI), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Perception, Action, Cognition pour la Conception et l’Ergonomie (PACCE), Laboratoire des Sciences du Numérique de Nantes (LS2N), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), Institute for Creative Technologies (ICT), University of Southern California (USC), CNRS, Université Toulouse Jean Jaurès, Université de Bordeaux, and Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST)

Subjects
stress, [SHS.SOCIO]Humanities and Social Sciences/Sociology, [SCCO.NEUR]Cognitive science/Neuroscience, signaux physiologique, [SCCO.PSYC]Cognitive science/Psychology, [SCCO.COMP]Cognitive science/Computer science, [SHS.PSY]Humanities and Social Sciences/Psychology, publics virtuels, Prise de parole en public, entraînement social
Abstract

International audience; Des agents virtuels peuvent être utilisés pour recréer des situations de prise de parole en public simulées devant un public virtuel. En psychothérapie, de tels publics virtuels ont été utilisés pour lutter contre l’anxiété à la prise de parole en public, des études préliminaires montrant leurs bénéfices potentiels. Des travaux récents ont étudié comment les comportements de publics virtuels sont perçus par des utilisateurs. Cependant, nous ne savons toujours pas dans quelle mesure certains facteurs, tels que les comportements du public virtuel, ont un impact sur les utilisateurs lorsqu’ils interagissent dans ces simulations. Dans cet article, nous présentons une étude expérimentale pour étudier les états physiologiques d’utilisateurs ainsi que leurs auto-évaluations lors d’interactions avec un public virtuel. Nous observons que les comportements du public virtuel n’ont pas influencé les auto-évaluations des participants ni leurs réponses physiologiques, qui étaient ici plutôt déterminées en premier lieu par le niveau d’anxiété pré-éxistant des participants.

Published
2020

36. Vers un système de production de feedbacks personnalisé pour l'entraînement de la prise de parole en public

Author

Fourati, Nesrine, Chollet, Mathieu, Umanis (Umanis), Groupe Umanis, Perception, Action, Cognition pour la Conception et l’Ergonomie (PACCE), Laboratoire des Sciences du Numérique de Nantes (LS2N), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), Département Automatique, Productique et Informatique (IMT Atlantique - DAPI), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), CNRS, Université Toulouse Jean Jaurès, Université de Bordeaux, and Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST)

Subjects
Prise de Parole en Public, [SHS.SOCIO]Humanities and Social Sciences/Sociology, Entraînement Social, [SCCO.NEUR]Cognitive science/Neuroscience, [SCCO.PSYC]Cognitive science/Psychology, [SCCO.COMP]Cognitive science/Computer science, [SHS.PSY]Humanities and Social Sciences/Psychology
Abstract

International audience; Motivés par le besoin de former les collaborateurs d’entreprises du secteur industriel, nous présentons un système de production de feedbacks pour l’entraînement de la prise de parole en public. Dans un premier temps, la description de la performance est réduite à l’expression vocale.

Published
2020

44. NADiA

Author

Wu, Jason, primary, Ghosh, Sayan, additional, Chollet, Mathieu, additional, Ly, Steven, additional, Mozgai, Sharon, additional, and Scherer, Stefan, additional

Published
2018
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46. Probing Dynamics in Colloidal Crystals with Pump-Probe Experiments at LCLS: Methodology and Analysis

Author

Vartaniants, Ivan, Mukharamova, Nastsia, Lazarev, Sergey, Meijer, Janne-Mieke, Chollet, Mathieu, Singer, Andrej, Kurta, Ruslan, Dzhigaev, Dmitry, Gorobtsov, Oleg, Williams, Garth, Zhu, Diling, Feng, Yiping, Sikorski, Marcin, Song, Sanghoon, Shabalin, Anatoly, Gurieva, Tatiana, Sulyanova, Elena, and Yefanov, Oleksandr

Subjects
lcsh:T, Physics::Optics, dynamics, lcsh:Technology, lcsh:QC1-999, lcsh:Chemistry, free-electron laser, pump-probe, lcsh:Biology (General), lcsh:QD1-999, lcsh:TA1-2040, colloidal crystal, lcsh:Engineering (General). Civil engineering (General), ddc:600, lcsh:QH301-705.5, lcsh:Physics
Abstract

Seminar, Hamburg, Germany ; Applied Sciences 7(5), 519 (2017). doi:10.3390/app7050519, We present results of the studies of dynamics in colloidal crystals performed by pump-probeexperiments using an X-ray free-electron laser (XFEL). Colloidal crystals were pumped with aninfrared laser at a wavelength of 800 nm with varying power and probed by XFEL pulses at anenergy of 8 keV with a time delay up to 1000 ps. The positions of the Bragg peaks, and their radialand azimuthal widths were analyzed as a function of the time delay. The spectral analysis of thedata did not reveal significant enhancement of frequencies expected in this experiment. Thisallowed us to conclude that the amplitude of vibrational modes excited in colloidal crystals was lessthan the systematic error caused by the noise level., Published by MDPI, Basel

Published
2017

47. Embodied Conversational Agents for social training: computational model for the expression of social attitudes through sequences of non-verbal signal

Author

Chollet, Mathieu, Chollet, Mathieu, Télécom ParisTech, Telecom Paristech, Catherine Pelachaud, and Magalie Ochs

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Social training, Agents Conversationnels Animés, Entrainement Social, [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC], [INFO.INFO-HC] Computer Science [cs]/Human-Computer Interaction [cs.HC], Embodied Conversational Agents, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

The Embodied Conversational Agents (ECAs) used in social training must be able to simulate all the different social situations that a learner has to train to. Depending on the application, the ECAs must then be able to express various emotions or various attitudes. Non-verbal signals, such as smiles or gestures, contribute to the expression of attitudes. However, recent findings have demonstrated that non-verbal signals are not interpretated in isolation but along with other signals : for instance, a smile followed by a gaze aversion and a head aversion does not signal amusement,but embarassment. Non-verbal behavior planning models for ECAs should thus consider complete sequences of non-verbal signals and not only signals independently of one another. However, existing models do not take this into account, or in a limited manner. The main contribution of this thesis is a methodology for the automatic extraction of sequences of non-verbal signals characteristic of attitude variations from a multimodal corpus, and a non-verbal behavior planning model that takes into account sequences of non-verbal signals rather than signals independently.Another consideration in the design of social training systems is to check that users do improve their social skills while using such systems. We investigated the use of ECAs to build a virtual audience aimed at improving users' public speaking skills. Another contribution of this thesis is the proposal of an architecture for interactive virtual audiences that provide realtime feedback to the learner according to his public speaking performance, and to have evaluated three different feedback strategies., Les développements récents dans le domaine des Agents Conversationnels Animés (ACAs), des personnages virtuels utilisant les modalités de la communication humaine (ex. gestes, parole) pour interagir avec un utilisateur, ont permis de proposer des systèmes pour l’entrainement des compétences sociales. Ces ACAs ont d’abord pris le rôle de tuteurs, ou de compagnons d’apprentissage, mais de nouvelles approches proposent l’utilisation des personnages virtuels afin de pratiquer ces compétences sociales en situation. Le projet Tardis propose par exemple d’utiliser un ACA dans le rôle d’un recruteur virtuel afin de s’entrainer à passer des entretiens d’embauche. Les contributions de cette thèse concernent deux enjeux de la conception de systèmes d’entrainement social par la mise en situation à l’aide d’ACAs.Les ACAs utilisés dans l’entrainement social doivent être capables de confronter l’apprenant à toutes les situations sociales nécessaires à son apprentissage. Selon l’application, les ACAs doivent ainsi pouvoir exprimer différentes émotions ou différentes attitudes. Les émotions et attitudes s’expriment en particulier par les signaux non-verbaux : sourires, postures, etc. Des recherches en psychologie ont cependant montré que l’interprétation de signaux non-verbaux est modifiée par les signaux proches : un sourire suivi d’un évitement de regard et d’un détournement de latête n’est ainsi pas un signe d’amusement mais d’embarras. Lors de la planification des signaux non-verbaux d’un ACA, il faut donc considérer les séquences complètes de signaux non-verbaux et pas seulement ces signaux indépendamment. Or, la plupart des modèles existants ne prennent pas cela en compte, ou de manière limitée.La contribution principale de notre thèse est de proposer une méthodologie pour extraire automatiquement d’un corpus multimodal des séquences de signaux nonverbaux caractéristiques d’un phénomène socio-émotionnel étudié, et un modèle de planification de signaux non-verbaux utilisant un ensemble de séquences extraites avec cette méthode. Nous appliquons ces travaux à l’expression d’attitudes sociales par un recruteur virtuel. Une autre enjeu dans la conception de systèmes d’entrainement social est de vérifier si les utilisateurs améliorent bien leurs compétences sociales en s’entrainant avec de tels systèmes. Nous nous sommes intéressés à la réalisation d’une audience virtuelle constituée d’ACAs servant à s’entrainer à l’entrainement à la prise de parole en public. Notre seconde contribution est d’avoir proposé une architecture d’audience virtuelle réagissant en temps réel à la performance de l’utilisateur, et d’avoir évalué plusieurs stratégies de retour à l’utilisateur.

Published
2015

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