Abstract. MPML3D is our first candidate of the next generation of authoring languages aimed at supporting digital content creators in providing highly appealing and highly interactive content with little effort. The language is based on our previously developed family of Multimodal Presentation Markup Languages (MPML) that broadly followed the “sequential” and “parallel ” tagging structure scheme for generating presynchronized presentations featuring life-like characters and interactions with the user. The new markup language MPML3D deviates from this design framework and proposes a reactive model instead, which is apt to handle interaction-rich scenarios with highly realistic 3D characters. Interaction in previous versions of MPML could be handled only at the cost of considerable scripting effort due to branching. By contrast, MPML3D advocates a reactive model that allows perceptions of other characters or the user interfere with the presentation flow at any time, and thus facilitates natural and unrestricted interaction. MPML3D is designed as a powerful and flexible language that is easy-to-use by non-experts, but it is also extensible as it allows content creators to add functionality such as a narrative model by using popular scripting languages. 1

We present ERIC, an affective embodied agent for realtime commentary in many domains. The underlying architecture is rulebased, generic, and lightweight – based on Java/Jess modules. Apart from reasoning about dynamically changing events, the system can produce coherent natural language and non-verbal behaviour, based on a layered model of affect (personality, mood, emotion). We show how reasoning, template-based natural language generation and affective appraisal can be implemented within the same rulebased paradigm. To make the system domain independent we worked on two different domains, a virtual horse race and a multiplayer tank battle game. We empirically evaluated the genericness of the system by measuring the effort it takes to change the domain, and discuss the results.

In this paper we introduce a system that automatically adds different types of non-verbal behavior to a given dialogue script between two virtual embodied agents. It allows us to transform a dialogue in text format into an agent behavior script enriched by eye gaze and conversational gesture behavior. The agents ’ gaze behavior is informed by theories of human face-to-face gaze behavior. Gestures are generated based on the analysis of linguistic and contextual information of the input text. The resulting annotated dialogue script is then transformed into the Multimodal Presentation Markup Language for 3D agents (MPML3D), which controls the multi-modal behavior of animated life-like agents, including facial and body animation and synthetic speech. Using our system makes it very easy to add appropriate non-verbal behavior to a given dialogue text, a task that would otherwise be very cumbersome and time consuming.

Abstract. In this paper we introduce a system that automatically adds different types of non-verbal behavior to a given dialogue script between two virtual embodied agents. It allows us to transform a dialogue in text format into an agent behavior script enriched by eye gaze and conversational gesture behavior. The agents ’ gaze behavior is informed by theories of human face-to-face gaze behavior. Gestures are generated based on the analysis of linguistic and contextual information of the input text. The resulting annotated dialogue script is then transformed into the Multimodal Presentation Markup Language for 3D agents (MPML3D), which controls the multi-modal behavior of animated life-like agents, including facial and body animation and synthetic speech. Using our system makes it very easy to add appropriate non-verbal behavior to a given dialogue text, a task that would otherwise be very cumbersome and time consuming. In order to test the quality of gaze generation, we conducted an empirical study. The results showed that by using our system, the naturalness of the agents ’ behavior was not increased when compared to randomly 1 selected gaze behavior, but the quality of the communication 2 between the two agents was perceived as significantly enhanced. 1

Life-like characters are one of the most exciting technologies for human– computer interface applications. They convincingly take the roles of virtual presenters, synthetic actors and sales personas, teammates and tutors. A common characteristic underlying their believability or life-likeness as conversational partners is computational models that provide them with affective functions such as synthetic emotions and personalities, and implement human interactive behavior or presentation skills. In social computing, a paradigm that aims to support the tendency of humans to interact with computers as social actors, life-like characters are key. They may embody the interface between humans and computers, and thus improve the otherwise poor communicative capabilities of computational devices. The success of life-like character applications today relies relies on the careful crafting of their designers, mostly programmers. The wide dissemination of life-like character technology in interactive systems, however, will greatly depend on the availability of tools that facilitate scripting of intelligent life-like behavior. The core tasks include the synchronization of synthetic speech and gestures, the expression

Abstract. This research proposes 3D graphical agents in the role of virtual presenters with a new type of functionality – the capability to process and respond to visual attention of users communicated by their eye movements. Eye gaze is an excellent clue to users ’ attention, visual interest, and visual preference. Using state-of-the-art non-contact eye tracking technology, eye movements can be assessed in a unobtrusive way. By analyzing and interpreting eye behavior in real-time, our proposed system can adapt to the current (visual) interest state of the user, and thus provide a more personalized, context-aware, and ‘attentive’ experience of the presentation. The system implements a virtual presentation room, where research content of our institute is presented by a team of two highly realistic 3D agents in a dynamic and interactive way. A small preliminary study was conducted to investigate users ’ gaze behavior with a non-interactive version of the system. A demo video based on our system was awarded as the best application of life-like agents at the GALA event in 2006. 1 1

User information is needed by adaptive systems in order to tailor information and product offers to the needs and preferences of individual users. Personalized Recommender Systems are adaptive systems that automatically generate recommendations on the basis of individual user profiles. Most existing Recommender Systems, however, are based on rather simple and mainly standardized profile information, which often delimits the adequacy of the recommendations they generate for an individual user. More adequate recommendations could be generated on the basis of more individual and representative user profiles that also integrate complex information, for example about personal interests or lifestyle. Furthermore, most adaptive systems acquire profile information only for their own purposes and do not allow for an exchange of this information with other applications the user wants to use. Above all, existing explicit profiling methods suffer from severe drawbacks which limit their utilizability in practice.

In this paper, we present a prototype that helps visualizing the relative importance of sentences extracted from medical texts using Embodied Conversational Agents (ECA). We propose to map rhetorical structures automatically recognized in the documents onto a set of communicative acts controlling the expression of an ECA. As a consequence, the ECA will dramatize a sentence to reflect its perceived importance and rhetorical strength (advice, requirement, open proposal, etc). This prototype is constituted of three sub-systems: i) G-DEE, a text analysis module ii) a mapping module which converts rhetorical structures produced by the text analysis module into communicative functions driving the ECA animation and iii) an ECA system. By bringing the text to life, this system could help their authors (in our application, expert physicians) to reflect on the potential impact of the writing style they have adopted. The use of ECA reintroduces an affective element which cannot easily be captured by other methods for analyzing document’s style.

Abstract not found