704 research outputs found
Expressing social attitudes in virtual agents for social training games
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
Vers des Agents Conversationnels Animés dotés d'émotions et d'attitudes sociales
International audienceIn this article, we propose an architecture of a socio-affective Embodied Conversational Agent (ECA). The different computational models of the architecture enable an ECA to express emotions and social attitudes during an interaction with a user. Based on corpora of actors expressing emotions, models have been defined to compute the emotional facial expressions of an ECA and the characteristics of its corporal movements. A user-perceptive approach has been used to design models to define how an ECA should adapt its non-verbal behavior according to the social attitude the ECA wants to display and the behavior of its interlocutor. The emotions and the social attitudes to express are computed by cognitive models presented in this article.Dans cet article, nous proposons une architecture d'un Agent Conversationnel Animé (ACA) socio-affectif. Les différents modèles computationnels sous-jacents à cette architecture, permettant de donner la capacité à un ACA d'exprimer des émotions et des attitudes sociales durant son interaction avec l'utilisateur, sont présentés. A partir de corpus d'individus exprimant des émotions, des modèles permettant de calculer l'expression faciale émotionnelle d'un ACA ainsi que les caractéristiques de ses mouvements du corps ont été définis. Fondés sur une approche centrée sur la perception de l'utilisateur, des modèles permettant de calculer comment un ACA doit adapter son comportement non-verbal suivant l'attitude sociale qu'il souhaite exprimer et suivant le comportement de son interlocuteur ont été construits. Le calcul des émotions et des attitudes sociales à exprimer est réalisé par des modèles cognitifs présentés dans cet article
A Multimodal Approach to Sarcasm Detection on Social Media
In recent times, a major share of human communication takes place online. The main reason being the ease of communication on social networking sites (SNSs). Due to the variety and large number of users, SNSs have drawn the attention of the computer science (CS) community, particularly the affective computing (also known as emotional AI), information retrieval, natural language processing, and data mining groups. Researchers are trying to make computers understand the nuances of human communication including sentiment and sarcasm. Emotion or sentiment detection requires more insights about the communication than it does for factual information retrieval. Sarcasm detection is particularly more difficult than categorizing sentiment. Because, in sarcasm, the intended meaning of the expression by the user is opposite to the literal meaning. Because of its complex nature, it is often difficult even for human to detect sarcasm without proper context. However, people on social media succeed in detecting sarcasm despite interacting with strangers across the world. That motivates us to investigate the human process of detecting sarcasm on social media where abundant context information is often unavailable and the group of users communicating with each other are rarely well-acquainted. We have conducted a qualitative study to examine the patterns of users conveying sarcasm on social media. Whereas most sarcasm detection systems deal in word-by-word basis to accomplish their goal, we focused on the holistic sentiment conveyed by the post. We argue that utilization of word-level information will limit the systems performance to the domain of the dataset used to train the system and might not perform well for non-English language. As an endeavor to make our system less dependent on text data, we proposed a multimodal approach for sarcasm detection. We showed the applicability of images and reaction emoticons as other sources of hints about the sentiment of the post. Our research showed the superior results from a multimodal approach when compared to a unimodal approach. Multimodal sarcasm detection systems, as the one presented in this research, with the inclusion of more modes or sources of data might lead to a better sarcasm detection model
The recognition of acted interpersonal stance in police interrogations and the influence of actor proficiency
This paper reports on judgement studies regarding the perception of interpersonal stances taken by humans playing the role of a suspect in a police interrogation setting. Our project aims at building believable embodied conversational characters to play the role of suspects in a serious game for learning interrogation strategies. The main question we ask is: do human judges agree on the way they perceive the various aspects of stance taking, such as friendliness and dominance? Four types of stances were acted by eight amateur actors. Short recordings were shown in an online survey to subjects who were asked to describe them using a selection of a number of adjectives. Results of this annotation task are reported in this paper. We explain how we computed the inter-rater agreement with Krippendorff’s alpha statistics using a set theoretical distance metric. Results show that for some of the stance types observers agreed more than for others. Some actors are better than others, but validity (recognizing the intended stance) and inter-rater agreement do not always go hand in hand. We further investigate the effect the expertise of actors has on the perception of the stance that is acted. We compare the fragments from amateur actors to fragments from professional actors taken from popular TV-shows
Computational Sociolinguistics: A Survey
Language is a social phenomenon and variation is inherent to its social
nature. Recently, there has been a surge of interest within the computational
linguistics (CL) community in the social dimension of language. In this article
we present a survey of the emerging field of "Computational Sociolinguistics"
that reflects this increased interest. We aim to provide a comprehensive
overview of CL research on sociolinguistic themes, featuring topics such as the
relation between language and social identity, language use in social
interaction and multilingual communication. Moreover, we demonstrate the
potential for synergy between the research communities involved, by showing how
the large-scale data-driven methods that are widely used in CL can complement
existing sociolinguistic studies, and how sociolinguistics can inform and
challenge the methods and assumptions employed in CL studies. We hope to convey
the possible benefits of a closer collaboration between the two communities and
conclude with a discussion of open challenges.Comment: To appear in Computational Linguistics. Accepted for publication:
18th February, 201
Language games and nature: a corpus-based analysis of ecological discourse
This dissertation approaches environmental discourse from the perspective of intercultural communication research. As a discipline, intercultural communication has encompassed a range of analytical levels, from micro-analysis of everyday communicative interactions to the macro-level structural factors that were brought into light by the critical turn. In light of planetary environmental issues, some researchers have called for an “ecological turn” as a new research paradigm. However, the complexity of integrating communication, culture, and the natural world into a coherent research program poses significant conceptual and methodological challenges. This dissertation seeks to provide both a methodological and conceptual framework for discourse at the interface of human cultures and the natural world
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