41,387 research outputs found
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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
An End-to-End Conversational Style Matching Agent
We present an end-to-end voice-based conversational agent that is able to
engage in naturalistic multi-turn dialogue and align with the interlocutor's
conversational style. The system uses a series of deep neural network
components for speech recognition, dialogue generation, prosodic analysis and
speech synthesis to generate language and prosodic expression with qualities
that match those of the user. We conducted a user study (N=30) in which
participants talked with the agent for 15 to 20 minutes, resulting in over 8
hours of natural interaction data. Users with high consideration conversational
styles reported the agent to be more trustworthy when it matched their
conversational style. Whereas, users with high involvement conversational
styles were indifferent. Finally, we provide design guidelines for multi-turn
dialogue interactions using conversational style adaptation
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
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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
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