- Paris
Researchers have theoretically proposed that humans decode other individuals' emotions or elementary cognitive appraisals from particular sets of facial action units (AUs). However, only a few empirical studies have systematically tested... more
Researchers have theoretically proposed that humans decode other individuals' emotions or elementary cognitive appraisals from particular sets of facial action units (AUs). However, only a few empirical studies have systematically tested the relationships between the decoding of emotions/appraisals and sets of AUs, and the results are mixed. Furthermore, the previous studies relied on facial expressions of actors and no study used spontaneous and dynamic facial expressions in naturalistic settings. We investigated this issue using video recordings of facial expressions filmed unobtrusively in a real-life emotional situation, specifically loss of luggage at an airport. The AUs observed in the videos were annotated using the Facial Action Coding System. Male participants (n = 98) were asked to decode emotions (e.g., anger) and appraisals (e.g., suddenness) from facial expressions. We explored the relationships between the emotion/appraisal decoding and AUs using stepwise multiple regression analyses. The results revealed that all the rated emotions and appraisals were associated with sets of AUs. The profiles of regression equations showed AUs both consistent and inconsistent with those in theoretical proposals. The results suggest that (1) the decoding of emotions and appraisals in facial expressions is implemented by the perception of set of AUs, and (2) the profiles of such AU sets could be different from previous theories.
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Abstract Emotional expressions play a very important role in the interaction between virtual agents and human users. In this paper, we present a new constraint-based approach to the generation of multimodal emotional displays. The... more
Abstract Emotional expressions play a very important role in the interaction between virtual agents and human users. In this paper, we present a new constraint-based approach to the generation of multimodal emotional displays. The displays generated with our method are not limited to the face, but are composed of different signals partially ordered in time and belonging to different modalities. We also describe the evaluation of the main features of our approach.
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The exploration of how we react to the world and interact with it and each other remains one of the greatest scientific challenges. Latest research trends in cognitive sciences argue that our common view of intelligence is too narrow,... more
The exploration of how we react to the world and interact with it and each other remains one of the greatest scientific challenges. Latest research trends in cognitive sciences argue that our common view of intelligence is too narrow, ignoring a crucial range of abilities that matter immensely for how people do in life. This range of abilities is called social intelligence and includes the ability to express and recognise social signals produced during social interactions like agreement, politeness, empathy, friendliness, conflict, etc., coupled with the ability to manage them in order to get along well with others while winning their cooperation. Social Signal Processing (SSP) is the new research domain that aims at understanding and modelling social interactions (human-science goals), and at providing computers with similar abilities in human–computer interaction scenarios (technological goals). SSP is in its infancy, and the journey towards artificial social intelligence and socially aware computing is still long. This research agenda is twofold, a discussion about how the field is understood by people who are currently active in it and a discussion about issues that the researchers in this formative field face.
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The ease and robustness of human-human communication is due to extremely high recognition accuracy (using multiple input channels) and the redundant and complimentary use of several modalities. Research in multimodal systems is based on... more
The ease and robustness of human-human communication is due to extremely high recognition accuracy (using multiple input channels) and the redundant and complimentary use of several modalities. Research in multimodal systems is based on the expectation that human-computer interaction can benefit from modeling several modalities in analogous ways.
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Research Interests: Artificial Intelligence, Human Computer Interaction, Affective Computing, Speech Recognition, Nonverbal Behavior, and 10 moreDialogue System, Software Agents, Emotional Computing, Emotion Recognition, Real Time Systems, Spoken Language Understanding, Real Time, User Behavior, Kansei Engineering, and Type System
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Research Interests: Information Systems, Computer Science, Human Computer Interaction, Gesture, Augmented Reality, and 14 moreUser Interface, Face, Virtual Worlds, Speech Processing, Speech, Computers and Society, Artificial Intelligent, Lecture notes, Standardisation, Audio Visual, Technological Development, Computers and Education, Human Machine Interaction, and Information System
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Abstract—In this project, which lies at the intersection between Human-Robot Interaction (HRI) and Human-Computer Interaction (HCI), we have examined the design of an open-source, real-time software platform for controlling the feedback... more
Abstract—In this project, which lies at the intersection between Human-Robot Interaction (HRI) and Human-Computer Interaction (HCI), we have examined the design of an open-source, real-time software platform for controlling the feedback provided by an AIBO robot and/or by the GRETA Embodied Conversational Agent, when listening to a story told by a human narrator. Based on ground truth data obtained from the recording and annotation of an audio-visual storytelling database, and containing various examples of human-human ...
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Working with emotion-related states in technological contexts requires a standard representation format. Based on that premise, the W3C Emotion Incubator group was created to lay the foundations for such a standard. The paper reports on... more
Working with emotion-related states in technological contexts requires a standard representation format. Based on that premise, the W3C Emotion Incubator group was created to lay the foundations for such a standard. The paper reports on two results of the group’s work: a collection of use cases, and the resulting requirements. We compiled a rich collection of use cases, and grouped them into three types: data annotation, emotion recognition, and generation of emotion-related behaviour. Out of these, a structured set of requirements was distilled. It comprises the representation of the emotion-related state itself, some meta-information about that representation, various kinds of links to the “rest of the world”, and several kinds of global metadata. We summarise the work, and provide pointers to the working documents containing full details.
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Developing an embodied conversational agent that is able to exhibit a human-like behavior while communicating with other virtual or human agents requires enriching a typical NLG architecture. The purpose of this paper is to describe our... more
Developing an embodied conversational agent that is able to exhibit a human-like behavior while communicating with other virtual or human agents requires enriching a typical NLG architecture. The purpose of this paper is to describe our efforts in this direction and to illustrate our approach to the generation of an Agent that shows a personality, a social intelligence and is able to react emotionally to events occurring in the environment, consistently with her goals and with the context in which the conversation takes place.
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this paper we first describe our enriched discourse generator explaining the 2 sets of rules (trigger and regulation) we have added. We also review the di# erent types of gaze communicative acts. Finally we present the variables defining... more
this paper we first describe our enriched discourse generator explaining the 2 sets of rules (trigger and regulation) we have added. We also review the di# erent types of gaze communicative acts. Finally we present the variables defining the context and how they modify the computation of the display of the communicative acts.
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1.1. Les agents conversationnels expressifs Ces dernières années, on observe un intérêt croissant pour le développement d'agents conversationnels animés (ACA) exprimant des émotions. Les ACAs sont des agents virtuels capables de... more
1.1. Les agents conversationnels expressifs Ces dernières années, on observe un intérêt croissant pour le développement d'agents conversationnels animés (ACA) exprimant des émotions. Les ACAs sont des agents virtuels capables de communiquer de façon autonome avec un usager, que ce soit à travers des modes verbaux ou non-verbaux. L'intérêt pour le développement d'une expressivité affective crédible chez les ACAs est motivé par la recherche de l'amé-lioration de l'interaction homme-machine (voir chapitre 8 [OCH 09] et chapitre 9 [CAN 09]). Pour être capable d'exprimer des émotions, l'agent doit avoir accès à un modèle déterminant une communication pouvant être comprise par les humains, ainsi qu'avoir des capacités techniques de communiquer non-verbalement. Les études montrent que les humains communiquent leurs émotions à travers di-verses modalités à la fois, bien que ce soit le visage que l'on considère comme le site propice pour l'expression d...
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This volume brings together the advanced research results obtained by the European COST Action 2102 "Cross Modal Analysis of Verbal and Nonverbal Communication", primarily discussed at the PINK SSPnet-COST2102 International Conference on... more
This volume brings together the advanced research results obtained by the European COST Action 2102 "Cross Modal Analysis of Verbal and Nonverbal Communication", primarily discussed at the PINK SSPnet-COST2102 International Conference on Analysis of Verbal and Nonverbal Communication and Enactment: The Processing Issues, held in Budapest, Hungary, in September 2010. The 40 papers presented were carefully reviewed and selected for inclusion in the book. The volume is arranged into two scientific sections. The first section, Multimodal Signals: Analysis, Processing and Computational Issues, deals with conjectural and processing issues of defining models, algorithms, and heuristic strategies for data analysis, coordination of the data flow and optimal encoding of multi-channel verbal and nonverbal features. The second section, Verbal and Nonverbal Social Signals, presents original studies that provide theoretical and practical solutions to the modelling of timing synchronization between linguistic and paralinguistic expressions, actions, body movements, activities in human interaction and on their assistance for an effective human-machine interactions.