Object-oriented class libraries offer the potential for individual researchers to manage the large bodies of code generated in the experimental development of complex interactive systems. This article analyzes the structure of such a class library that supports the rapid prototyping of a wide range of systems including collaborative networking, shared documents, hypermedia, machine learning, knowledge acquisition and knowledge representation, and various combinations of these technologies. The overall systems architecture is presented in terms of a heterogeneous collection of systems providing a wide range of application functionalities. Examples are given of group writing, multimedia and knowledge-based systems which are based on combining these functionalities. The detailed design issues of the knowledge representation server component of the system are analyzed in terms of requirements, current state-of-the-art, and the underlying theoretical principles that lead to an effective obj...

Abstract — As low resolution shots, rotations of the head with respect to the camera, face deformation due to speech and so on inflict a great deal of uncertainty in FAP measurements, uncertainty is also inherent in the process of expression analysis. In this paper we tackle such uncertainty via the observation that user emotions do not typically alter rapidly very often. Thus, possibilistic evidence may be gathered from each frame about the user expression; evidence from the current and recent frames can be combined using evidence theory. I.

We present a classifier to predict contextual polarity of subjective phrases in a sentence. Our approach features lexical scoring derived from the Dictionary of Affect in Language (DAL) and extended through WordNet, allowing us to automatically score the vast majority of words in our input avoiding the need for manual labeling. We augment lexical scoring with n-gram analysis to capture the effect of context. We combine DAL scores with syntactic constituents and then extract n-grams of constituents from all sentences. We also use the polarity of all syntactic constituents within the sentence as features. Our results show significant improvement over a majority class baseline as well as a more difficult baseline consisting of lexical n-grams. 1

Abstract. The ability to simulate lifelike interactive characters has many applications in the gaming industry. A lifelike human face can enhance interactive applications by providing straightforward feedback to and from the users and stimulating emotional responses from them. Thus, the gaming and entertainment industries can benefit from employing believable, expressive characters since such features significantly enhance the atmosphere of a virtual world and communicate messages far more vividly than any textual or speech information. In this paper, we present an abstract means of description of facial expressions, by utilizing concepts included in the MPEG-4 standard. Furthermore, we exploit these concepts to synthesize a wide variety of expressions using a reduced representation, suitable for networked and lightweight applications. 1

Abstract. The SALERO project observed a lack of ontologies for the description and annotation of characters in media production. In this field ontologies could be used to support media asset management, information retrieval, automated production or reuse. This paper presents the SALERO Virtual Character Ontology which can be used to describe and annotate characters in media production and game design to support aforementioned scenarios. 1

Abstract. We report work in progress on adding affect-detection to an existing e-drama program, a text-based software system for (human) dramatic improvisation in simple virtual scenarios, for use primarily in learning contexts. The system allows a human director to monitor improvisations and make interventions, for instance in reaction to excessive, insufficient or inappropriate emotions in the characters ’ speeches. Within an endeavour to partially automate directors ’ functions, and to allow for automated affective bit-part characters, we have developed a prototype affect-detection module. It is aimed at detecting affective aspects (concerning emotions, moods, rudeness, value judgments, etc.) of human-controlled characters ’ textual “speeches”. The detection is necessarily relatively shallow, but the work accompanies basic research into how affect is conveyed linguistically. A distinctive feature of the project is a focus on the metaphorical ways in which affect is conveyed. The paper is relevant to the following Workshop themes: significance of affect in learning contexts; affective companions; diagnosis of affect; what types of affect we need to be concerned about; meta-emotion; and requirements for affect/cognition modelling.

This paper begins to answer the call to broaden current theories of individual decision-making by including in them the effects of human mood. Grounding our arguments in psychological literature on the effects of mood on information processing, motivation, and decision heuristics, we develop hypotheses about how mood can significantly affect individuals' use of structured decision protocols. In support of our hypotheses, results from an experimental study of complex decision-making suggest that, in situations where a structured decision protocol is the usual method of decision-making, individuals in moderately negative moods are significantly more likely than those in moderately positive moods to: (1) carefully execute all the steps of a structured decision protocol, (2) execute the steps of a structured decision protocol in the correct order, and (3) rely on the outcome of the structured decision protocol as the primary basis for the decision. We discuss these findings in terms of the...

Abstract This work is about multimodal and expressive synthesis on virtual agents, based on the analysis of actions performed by human users. As input we consider the image sequence of the recorded human behavior. Computer vision and image processing techniques are incorporated in order to detect cues needed for expressivity features extraction. The multimodality of the approach lies in the fact that both facial and gestural aspects of the user’s behavior are analyzed and processed. The mimicry consists of perception, interpretation, planning and animation of the expressions shown by the human, resulting not in an exact duplicate rather than an expressive model of the user’s original behavior.

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