Emphatic agents to reduce user frustration: The effects of varying agent characteristics

There is now growing interest in the development of computer systems which respond to users’ emotion and affect. We report three small scale studies (with a total of 42 participants) which investigate the extent to which affective agents, using strategies derived from human-human interaction, can reduce user frustration within human-computer interaction. The results confirm the previous findings of Klein et al (2002) that such interventions can be effective. We also obtained results that suggest that embodied agents can be more effective at reducing frustration than non-embodied agents, and that female embodied agents may be more effective than male embodied agents. These results are discussed in light of the existing research literature

Towards Learning ‘Self’ and Emotional Knowledge in Social and Cultural Human-Agent Interactions

Original article can be found at: http://www.igi-global.com/articles/details.asp?ID=35052 Copyright IGI. Posted by permission of the publisher.This article presents research towards the development of a virtual learning environment (VLE) inhabited by intelligent virtual agents (IVAs) and modeling a scenario of inter-cultural interactions. The ultimate aim of this VLE is to allow users to reflect upon and learn about intercultural communication and collaboration. Rather than predefining the interactions among the virtual agents and scripting the possible interactions afforded by this environment, we pursue a bottomup approach whereby inter-cultural communication emerges from interactions with and among autonomous agents and the user(s). The intelligent virtual agents that are inhabiting this environment are expected to be able to broaden their knowledge about the world and other agents, which may be of different cultural backgrounds, through interactions. This work is part of a collaborative effort within a European research project called eCIRCUS. Specifically, this article focuses on our continuing research concerned with emotional knowledge learning in autobiographic social agents.Peer reviewe

Empathic Agent Technology (EAT)

A new view on empathic agents is introduced, named: Empathic Agent Technology (EAT). It incorporates a speech analysis, which provides an indication for the amount of tension present in people. It is founded on an indirect physiological measure for the amount of experienced stress, defined as the variability of the fundamental frequency of the human voice. A thorough review of literature is provided on which the EAT is founded. In addition, the complete processing line of this measure is introduced. Hence, the first generally applicable, completely automated technique is introduced that enables the development of truly empathic agents

Guide to the Networked Minds Social Presence Inventory v. 1.2

This document introduces the Networked\ud Minds Social Presence Inventory. The\ud inventory is a self-report measure of social\ud presence, which is commonly defined as the\ud sense of being together with another in a\ud mediated environment. The guidelines\ud provide background on the use of the social\ud presence scales in studies of users’ social\ud communication and interaction with other\ud humans or with artificially intelligent agents\ud in virtual environments

Effective Tutoring with Empathic Embodied Conversational Agents

This thesis examines the prospect of using empathy in an Embodied Tutoring System (ETS) that guides students through an online quiz (by providing feedback on student answers and responding to self-reported student emotion). The ETS seeks to imitate human behaviours successfully used in one-to-one human tutorial interactions. The main hypothesis is that the interaction with an empathic ETS results in greater learning gains than a neutral ETS, primarily by encouraging positive and reducing negative student emotions using empathic feedback. In a preparatory study we investigated different strategies for expressing emotion by the ETS. We established that a multimodal strategy achieves the best results regarding how accurately human participants can recognise the emotions. This approach was used in developing the feedback strategy for our empathic ETS. The preparatory study was followed by two studies in which we compared a neutral with an empathic ETS. The ETS in the second of these studies was developed using results from the first of these studies. In both studies, we found no statistically significant difference in learning gains between the neutral and empathic ETS. However, we did discover a number of interactions between the ETS system, learning gains and, in particular 1) student scores on an empathic tendency test and 2) student ability. We also analysed the subjective responses and the relation between self-reported emotions during the quiz and student learning gains. Based on our studies in a formal class room setting, we assess the prospects of using empathic agents in a classroom setting and describe a number of requirements for their effective use

Usability and acceptability assessment of an empathic virtual agent to prevent major depression

In Human-Computer Interaction, the adaptation of the content and the way of how this content is communicated to the users in interactive sessions is a critical issue to promote the acceptability and usability of any computational system. We present a user-adapted interactive platform to identify and provide an early intervention for symptoms of depression and suicide. In particular, we describe the work performed to assess users' system acceptability and usability. An empathic Virtual Agent is the main interface with the user, and it has been designed to generate the appropriate dialogues and emotions during the interactions according to the detected user's specific needs. This personalization is based on a dynamic user model nurtured with clinical, demographical and behavioural information. The evaluation was performed with 60 participants from the university community. The obtained results were promising, allowing the execution of a further clinical trial. The system's usability score was 75.7%, and the score of the user-adapted content and the emotional responses of the Virtual Agent was 70.9%.The work presented in this manuscript has been partially funded by the Conselleria de Sanidad of Generalitat Valenciana, in the research project entitled 'Sistema computacional de ayuda a la prevencion de episodios de depresion y suicidio - PREVENDEP'. We thank the company Faceshift (www.faceshift.com) for providing their software to perform facial motion capture in order to develop the talking head that represent our empathic virtual agent.Bresó Guardado, A.; Martinez-Miranda, J.; Botella Arbona, C.; Baños Rivera, RM.; García Gómez, JM. (2016). Usability and acceptability assessment of an empathic virtual agent to prevent major depression. Expert Systems. 33(4):297-312. doi:10.1111/exsy.12151S29731233

Adapting Progress Feedback and Emotional Support to Learner Personality

Peer reviewedPostprin

A dataset of continuous affect annotations and physiological signals for emotion analysis

From a computational viewpoint, emotions continue to be intriguingly hard to understand. In research, direct, real-time inspection in realistic settings is not possible. Discrete, indirect, post-hoc recordings are therefore the norm. As a result, proper emotion assessment remains a problematic issue. The Continuously Annotated Signals of Emotion (CASE) dataset provides a solution as it focusses on real-time continuous annotation of emotions, as experienced by the participants, while watching various videos. For this purpose, a novel, intuitive joystick-based annotation interface was developed, that allowed for simultaneous reporting of valence and arousal, that are instead often annotated independently. In parallel, eight high quality, synchronized physiological recordings (1000 Hz, 16-bit ADC) were made of ECG, BVP, EMG (3x), GSR (or EDA), respiration and skin temperature. The dataset consists of the physiological and annotation data from 30 participants, 15 male and 15 female, who watched several validated video-stimuli. The validity of the emotion induction, as exemplified by the annotation and physiological data, is also presented.Comment: Dataset available at: https://rmc.dlr.de/download/CASE_dataset/CASE_dataset.zi