Emotions play a critical role in creating engaging and believable characters to populate virtual worlds. Our goal is to create general computational models to support characters that act in virtual environments, make decisions, but whose behavior also suggests an underlying emotional current. In service of this goal, we integrate two complementary approaches to emotional modeling into a single unified system. Gratch's mile system focuses on the problem of emotional appraisal: how emotions arise from an evaluation of how environmental events relate to an agent's plans and goals. Marsella et al.'s IPD system focuses more on the impact of emotions on behavior, including the impact on the physical expressions of emotional state through suitable choice of gestures and body language. This integrated model is layered atop Steve, a pedagogical agent architecture, and exercised within the context of the Mission Rehearsal Exercise, a prototype system designed to teach decision-making skills in highly evocative situations.

Researchers studying autonomous agents are increasingly examining the problem of integrating multiple capabilities into single agents. The Oz project is developing technology for dramatic, interactive, simulated worlds. One requirement of such worlds is the presence of broad, though perhaps shallow, agents. To support our needs, we are developing an agent architecture, called Tok, that displays reactivity, goal-directed behavior, and emotion, along with other capabilities. Integrating the components of Tok into a coherent whole raises issues of how the parts interact, and seems to place constraints on the nature of each component. Here we describe briefly the integration issues we have encountered in building a particular Tok agent (Lyotard the cat), note their impact on the architecture, and suggest that modeling emotion, in particular, may constrain the design of integrated agent architectures.

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In this paper we present a linguistic resource for the lexical representation of affective knowledge. This resource (named WORDNET-AFFECT) was developed starting from WORDNET, through a selection and tagging of a subset of synsets representing the affective meanings. 1.

Abstract—The importance of automatically recognizing emotions from human speech has grown with the increasing role of spoken language interfaces in human-computer interaction applications. This paper explores the detection of domain-specific emotions using language and discourse information in conjunction with acoustic correlates of emotion in speech signals. The specific focus is on a case study of detecting negative and non-negative emotions using spoken language data obtained from a call center application. Most previous studies in emotion recognition have used only the acoustic information contained in speech. In this paper, a combination of three sources of information—acoustic, lexical, and discourse—is used for emotion recognition. To capture emotion information at the language level, an information-theoretic notion of emotional salience is introduced. Optimization of the acoustic correlates of emotion with respect to classification error was accomplished by investigating different feature sets obtained from feature selection, followed by principal component analysis. Experimental results on our call center data show that the best results are obtained when acoustic and language information are combined. Results show that combining all the information, rather than using only acoustic information, improves emotion classification by 40.7 % for males and 36.4 % for females (linear discriminant classifier used for acoustic information). Index Terms—Acoustic correlates, dialog systems, emotion recognition, emotional salience, feature selection, information fusion, principal component analysis, spoken language processing. I.

The Oz project at Carnegie Mellon is developing technology for dramatic virtual worlds. One requirement of such worlds is the presence of broad, though perhaps shallow, agents. To support our needs, we are developing an agent architecture that provides goals and goal directed reactive behavior, emotional state and its effects on behavior, some natural language abilities (especially pragmatics based language generation), and some memory and inference abilities. We are limiting each of these capacities whenever necessary to allow us to build a broadly capable, integrated agent. In attempting to construct a broad agent, constraints seem to arise between components of the architecture. In this brief note, we discuss some of these constraints.

Research on speech and emotion is moving from a period of exploratory research into one where there is a prospect of substantial applications, notably in human–computer interaction. Progress in the area relies heavily on the development of appropriate databases. This paper addresses four main issues that need to be considered in developing databases of emotional speech: scope, naturalness, context and descriptors. The state of the art is reviewed. A good deal has been done to address the key issues, but there is still a long way to go. The paper shows how the challenge of developing appropriate databases is being addressed in three major recent projects––the Reading–Leeds project, the Belfast project and the CREST–ESPproject. From these and other studies the paper draws together the tools and methods that have been developed, addresses the problems that arise and indicates the future directions for the development of emotional speech databases.

This paper, an expanded version of a talk on love given to a literary society, attempts to analyse some of the architectural requirements for an agent which is capable of having primary, secondary and tertiary emotions, including being infatuated or in love. It elaborates on work done previously in the Birmingham Cognition and Affect group, describing our proposed three level architecture (with reactive, deliberative and metamanagement layers), showing how different sorts of emotions relate to those layers. Some of the relationships between emotional states involving partial loss of control of attention (e.g. emotional states involved in being in love) and other states which involve dispositions (e.g. attitudes such as loving) are discussed and related to the architecture. The work of poets and playwrights can be shown to involve an implicit commitment to the hypothesis that minds are (at least) information processing engines. Besides loving, many other familiar states and process...

There is much shallow thinking about emotions, and a huge diversity of definitions of “emotion ” arises out of this shallowness. Too often the definitions and theories are inspired either by a mixture of introspection and selective common sense, or by a misdirected neo-behaviourist methodology, attempting to define emotions and other mental states in terms of observables. One way to avoid such shallowness, and perhaps eventually achieve convergence, is to base concepts and theories on an information processing architecture, which is subject to various constraints, including evolvability, implementability, coping with resource-limited physical mechanisms, and human-like functionality. Within such an architecture-based theory we can distinguish (at least) primary emotions, secondary emotions, and tertiary emotions, and produce a coherent theory which explains a wide range of phenomena and also partly explains the diversity of theories: most theorists focus on only a subset of types of emotions.

Abstract. A growing number of research projects in academia and industry have recently started to develop lifelike agents as a new metaphor for highly personalised human-machine communication. A strong argument in favour of using such characters in the interface is the fact that they make humancomputer interaction more enjoyable and allow for communication styles common in human-human dialogue. Our earlier work in this area has concentrated on the development of animated presenters that show, explain, and verbally comment textual and graphical output on a window-based interface. Even though first empirical studies have been very encouraging and revealed a strong affective impact of our Personas [23], they also suggest that simply embodying an interface agent is insufficient. To come across as believable, an agent needs to incorporate a deeper model of personality and emotions, and in particular directly connect these two concepts.