We illustrate how the use of metaphorical views for reasoning with metaphor requires the mapping of information such as event shape, event rate and mental/emotional states from the source domain to the target domain. Such mappings are domain-independent and can be implemented by means of rules we call View Neutral Mapping Adjuncts (VNMAs). We give a list of the main VNMAs that appear to be required, and show how they can be incorporated into a pre-existing system (ATT-Meta) for metaphorical reasoning.

Abstract:We report work on adding affect-detection to an existing e-drama programme, 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 an affect-detection module. It is aimed at detecting affective aspects (concerning emotions, moods, rudeness, value judgments, etc.) of humancontrolled characters' textual 'speeches'. The work also 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 project addresses the special issue themes such as making interactive narrative learning environments more usable, building them, and supporting reflection on narrative construction.Keywords: affect detection; e-drama; intelligent virtual actor and metaphor.Reference to this paper should be made as follows: Zhang, L., Barnden, J.A., Hendley, R.J., Lee, M.G., Wallington, A.M. and Wen, Z. (2008) Professor John A. Barnden is leading the EPSRC/ESRC/DTI-funded project on 'e-drama', one aspect of which will draw on the metaphor processing research in the ATT-Meta project. His research interests mainly are Natural language Processing and Artificial Intelligence. He was a coproposer of a series of EURESCO conferences focusing on metaphor. He recently joined the organisational board of the Researching and Applying Metaphor (RAAM) series of international conferences. He was a keynote speaker at RAAM-IV in Dr. Zhigang Wen currently works as a research fellow in the e-drama project at the School of Computer Science, University of Birmingham. His main research interests include real time virtual human animation, gesture generation system, and natural language processing for 3D embodied conversational agent. He received an MSc in Computer Graphics and a PhD in real time virtual human animation.

We consider the varieties and directions of influence that the source and target domains involved in a conceptual metaphor can have on each other during the course of understanding metaphorical utterances based on the metaphor. Previous studies have been restricted both as to direction of influence and as to type of influence. They have been largely confined to the "forward" (source to target) direction of influence, and they have concentrated on the transfer of features or propositions and (to some extent) the highlighting of aspects of a domain. By contrast, this article stresses the importance both of other varieties of influence (e.g., transfer of queries and uncertainty effects) and of "reverse" influence (target to source). We seek to curb the natural tendency to think that, because metaphor involves an overall move from source to target, therefore all inter-domain influences in the course of understanding go in that direction. The bulk of the article explores the theoretical issues involved. These issues have arisen out of a reasoning-based approach to metaphor, seeking to make best use of information from metaphorical utterance, context, source and target domains, and known metaphorical mappings, by applying a complex overall reasoning process. The article briefly explains the thorough implementation of reverse influence in a computer program for metaphorical reasoning called ATT-Meta, although the theoretical considerations are relevant to all disciplines concerned with metaphor. We make some suggestions for further computational and psychological research on metaphor.2

We report progress on adding affectdetection to a program for virtual dramatic improvisation, monitored by a human director. We have developed an affect-detection module to control an automated virtual actor and to contribute to the automation of directorial functions. The work also involves basic research into how affect is conveyed through metaphor. The project contributes to the application of sentiment and subjectivity analysis to the creation of emotionally believable synthetic agents for interactive narrative environments.

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