21,015 research outputs found
RRL: A Rich Representation Language for the Description of Agent Behaviour in NECA
In this paper, we describe the Rich Representation Language (RRL) which is used in the NECA system. The NECA system generates interactions between two or more animated characters. The RRL is a formal framework for representing the information that is exchanged at the interfaces between the various NECA system modules
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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
Agent Assistance: From Problem Solving to Music Teaching
We report on our research on agents that act and behave in a web learning environment. This research is part of a general approach to agents acting and behaving in virtual environments where they are involved in providing information, performing transactions, demonstrating products and, more generally, assisting users or visitors of the web environment in doing what they want or have been asked to do. While initially we hardly provided our agents with 'teaching knowledge', we now are in the process of making such knowledge explicit, especially in models that take into account that assisting and teaching takes place in a visualized and information-rich environment. Our main (embodied) tutor-agent is called Jacob; it knows about the Towers of Hanoi, a well-known problem that is offered to CS students to learn about recursion. Other agents we are working on assist a visitor in navigating in a virtual world or help the visitor in getting information. We are now designing a music teacher - using knowledge of software engineering and how to design multi-modal interactions, from previous projects
A mobile fitness companion
The paper introduces a Mobile Companion prototype, which helps users to plan and keep track of their exercise activities via an interface based mainly on speech input and output. The Mobile Companion runs on a PDA and is based on a stand-alone, speaker-independent solution, making it fairly unique among mobile spoken dialogue systems, where the common solution is to run the ASR on a separate server or to restrict the speech input to some specific set of users. The prototype uses a GPS receiver to collect position, distance and speed data while the user is exercising, and allows the data to be compared to previous exercises. It communicates over the mobile network with a stationary system, placed in the user’s home. This allows plans for exercise activities to be downloaded from the stationary to the mobile system, and exercise result data to be uploaded once an exercise has been completed
Improvising Linguistic Style: Social and Affective Bases for Agent Personality
This paper introduces Linguistic Style Improvisation, a theory and set of
algorithms for improvisation of spoken utterances by artificial agents, with
applications to interactive story and dialogue systems. We argue that
linguistic style is a key aspect of character, and show how speech act
representations common in AI can provide abstract representations from which
computer characters can improvise. We show that the mechanisms proposed
introduce the possibility of socially oriented agents, meet the requirements
that lifelike characters be believable, and satisfy particular criteria for
improvisation proposed by Hayes-Roth.Comment: 10 pages, uses aaai.sty, lingmacros.sty, psfig.st
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