22,104 research outputs found
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Reference and Gestures in Dialogue Generation: Three Studies with Embodied Conversational Agents
This paper reports on three studies into social presence cues which were carried out in the context of the NECA (Net-environment for Embodied Emotional Conversational Agents) project and the EPOCH network. The first study concerns the generation of referring expressions. We adopted an existing algorithm for generating referring expressions such that it could run according to an egocentric and a neutral strategy. In an evaluation study, we found that the two strategies were correlated with the perceived friendliness of the speaker. In the second and the third study, we evaluated the gestures that were generated by the NECA system. In this paper, we briefly summarize the most salient results of these two studies. They concern the effect of gestures on perceived quality of speech and information retention
How the agentâs gender influence usersâ evaluation of a QA system
In this paper we present the results of a pilot study investigating the effects of agentsâ gender-ambiguous vs. gender-marked look on the perceived interaction quality of a multimodal question answering system. Eight test subjects interacted with three system agents, each having a feminine, masculine or gender-ambiguous look. The subjects were told each agent was representing a differently configured system. In fact, they were interacting with the same system. In the end, the subjects filled in an evaluation questionnaire and participated in an in-depth qualitative interview. The results showed that the user evaluation seemed to be influenced by the agentâs gender look: the system represented by the feminine agent achieved on average the highest evaluation scores. On the other hand, the system represented by the gender-ambiguous agent was systematically lower rated. This outcome might be relevant for an appropriate agent look, especially since many designers tend to develop gender-ambiguous characters for interactive interfaces to match various usersâ preferences. However, additional empirical evidence is needed in the future to confirm our findings
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Politeness and bias in dialogue summarization: two exploratory studies
In this chapter, two empirical pilot studies on the role of politeness in dialogue summarization are described. In these studies, a collection of four dialogues was used. Each dialogue was automatically generated by the NECA system and the politeness of the dialogue participants was
systematically manipulated. Subjects were divided into groups who had to summarize the dialogues from a particular dialogue participantâs point of view or the point of view of an impartial observer. In the first study, there were no other constraints. In the second study, the summarizers were restricted to summaries whose length did not exceed 10% of the number of words in the dialogue that was being summarized. Amongst other things, it was found that the politeness of the interaction is
included more often in summaries of dialogues that deviate from what would be considered normal or unmarked. A comparison of the results of the two studies suggests that the extent to which politeness is reported is not affected by how long a summary is allowed to be. It was also found that the point of view of the summarizer influences which information is included in the summary and how it is presented. This finding did not seem to be affected by the constraint in our second study on the summary length
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Generation of multi-modal dialogue for a net environment
In this paper an architecture and special purpose markup language for simulated affective face-to-face communication is presented. In systems based on this architecture, users will be able to watch embodied conversational agents interact with each other in virtual locations on the internet. The markup language, or Rich Representation Language (RRL), has been designed to provide an integrated representation of speech, gesture, posture and facial animation
A Review of Verbal and Non-Verbal Human-Robot Interactive Communication
In this paper, an overview of human-robot interactive communication is
presented, covering verbal as well as non-verbal aspects of human-robot
interaction. Following a historical introduction, and motivation towards fluid
human-robot communication, ten desiderata are proposed, which provide an
organizational axis both of recent as well as of future research on human-robot
communication. Then, the ten desiderata are examined in detail, culminating to
a unifying discussion, and a forward-looking conclusion
The use of animated agents in eâlearning environments: an exploratory, interpretive case study
There is increasing interest in the use of animated agents in eâlearning environments. However, empirical investigations of their use in online education are limited. Our aim is to provide an empirically based framework for the development and evaluation of animated agents in eâlearning environments. Findings suggest a number of challenges, including the multiple dialogue models that animated agents will need to accommodate, the diverse range of roles that pedagogical animated agents can usefully support, the dichotomous relationship that emerges between these roles and that of the lecturer, and student perception of the degree of autonomy that can be afforded to animated agents
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Simulating emotional reactions in medical dramas
Presenting information on emotionally charged topics is a delicate task: if bare facts alone are conveyed, there is a risk of boring the audience, or coming across as cold and unfeeling; on the other hand, emotional presentation can be appropriate when carefully handled, but when overdone or mishandled risks being perceived as patronising or in poor taste. When Natural Language Generation (NLG) systems present emotionally charged information linguistically, by generating scripts for embodied agents, emotional/affective aspects cannot be ignored. It is important to ensure that viewers consider the presentation appropriate and sympathetic.
We are investigating the role of affect in communicating medical information in the context of an NLG system that generates short medical dramas enacted by embodied agents. The dramas have both an informational and an educational purpose in that they help patients review their medical histories whilst receiving explanations of less familiar medical terms and demonstrations of their usage. The dramas are also personalised since they are generated from the patients' own medical records. We view generation of natural/appropriate emotional language as a way to engage and maintain the viewers' attention. For our medical setting, we hypothesize that viewers will consider dialogues more natural when they have an enthusiastic and sympathetic emotional tone. Our second hypothesis proposes that such dialogues are also better for engaging the viewers' attention.
As well as describing our NLG system for generating natural emotional language in medical dialogue, we present a pilot study with which we investigate our two hypotheses. Our results were not quite as unequivocal as we had hoped. Firstly, our participants did notice whether a character sympathised with the patient and was enthusiastic. This did not, however, lead them to judge such a character as behaving more naturally or the dialogue as being more engaging. However, when pooling data from our two conditions, dialogues with versus dialogues without emotionally appropriate language use, we discovered, somewhat surprisingly, that participants did consider a dialogue more engaging if they believed that the characters showed sympathy towards the patient, were not cold and unfeeling, and were natural (true for the female agent only)
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