Catálogo de publicaciones - libros

This paper presents a novel approach to Emotion Estimation that assesses the affective content from textual messages. Our main goals are to detect emotion from chat or other dialogue messages and to employ animated agents capable of the emotional reasoning based on the textual interaction. In this paper, the emotion estimation module is applied to a chat system, where avatars associated with chat partners act out the assessed emotions of messages through multiple modalities, including synthetic speech and associated affective gestures.

Human emotion is related to stimulus and cognitive appraisal. Emotion is very important to entertainment application of virtual reality. Emotion model of 3D virtual characters is a challenging branch of Intelligent Virtual Environment (IVE). A believable 3D character should be provided with emotion and perception. In general, a virtual character is regarded as an autonomous agent with sense, perception, behavior and action. An emotion model of 3D virtual characters on the basis of psychology theory is presented in this paper. Our work is to construct 3D virtual characters that have internal sensor and perception for external stimulus, and express emotion autonomously in real time. Firstly, architecture of a virtual character is set up by cognitive model; Secondly, emotion class is set up by OCC and Plutchik’s emotion theory; Thirdly, some new concepts about emotion are presented with a general mathematical model which is relation among emotion, stimulus, motivation variable, personality variable. Fourthly, a perception model of 3D characters by Gibson’s theory is introduced. As a result, an emotional animation demo system of 3D virtual character is implemented on PC.

Curtin University’s Talking Heads (TH) combine an MPEG-4 compliant Facial Animation Engine (FAE), a Text To Emotional Speech Synthesiser (TTES), and a multi-modal Dialogue Manager (DM), that accesses a Knowledge Base (KB) and outputs Virtual Human Markup Language (VHML) text which drives the TTES and FAE. A user enters a question and an animated TH responds with a believable and affective voice and actions. However, this response to the user is normally marked up in VHML by the KB developer to produce the required facial gestures and emotional display. A real person does not react by fixed rules but on personality, beliefs, good and bad previous experiences, and training. This paper reviews personality theories and models relevant to THs, and then discusses the research at Curtin over the last five years in implementing and evaluating personality models. Finally the paper proposes an active, adaptive personality model to unify that work.

The present study investigated the effect of mood on self-paced study time. Twenty-eight university students voluntarily participated in the experiment. Half of them listened to positive music and the other half listened to negative music for nine minutes. After self-assessment of mood, they made self-paced study for word-pairs. The results showed that negative and positive mood have not significant effect on self-paced study time.

This study investigates the influence of the speech quality of Embodied Conversational Agents (ECAs) on users’ perception, behavior and emotions. Twenty-four subjects interacted in a Wizard of Oz (WOZ) setup with two ECAs in two scenarios of a virtual theater partner application. In both scenarios, each ECA had three different speech qualities: natural, high-quality synthetic and low-quality synthetic. Eye gaze data show that subjects’ visual attention was not influenced by ECA’s speech quality, but by their look. On the other hand, subjects’ self-report of emotions and verbal descriptions of their perceptions were influenced by ECAs’ speech quality. Finally, Galvanic Skin Response data were neither influenced by ECAs’ look, nor by their speech quality. These results stress the importance of the correct matching of the auditory and visual modalities of ECAs and give methodological insights for the assessment of user’s perception, behavior and emotions when interacting with virtual characters.

For the purpose of processing data efficiently in the huge data environment, a design of intelligent system based on the function of human brain is necessary. This paper describes how to reconstruct the efficient subject memory considering the personal preference from the objective facts. Conceptual modeling of new knowledge reconfiguration based on the common node connection from a different memory is proposed. The well formed structure of knowledge frame with special synonym list was designed for the efficient knowledge reconfiguration, and using this structure Knowledge retrieval mechanism was made to perform extracting the associated data.We applied this mechanism to the supposed virtual knowledge frame and tested.

To endow the synthetic characters with autonomous behaviors interests several fields of researchers, especially the experts of computer graphics. In this paper, we propose a believable brain architecture to allow the synthetic character to achieve high level of autonomy. There are three new capabilities. Firstly, this architecture is not a simple stimulation-action model, but adds a layer between stimulation and action called agency that plays a role of extraction and synthesis. Secondly, hierarchy Finite State Machines (FSMs) and fuzzy logic techniques are embedded into the synthetic character’s brain. Finally, the ability to integrate the emotion expression model into the brain architecture allows the synthetic characters to express their sensibilities such as happy, angry, sorry, etc., which can inspire the users’ passion and fuse them into the virtual world.

HandWave is a small, wireless, networked skin conductance sensor for affective computing applications. It is used to detect information related to emotional, cognitive, and physical arousal of mobile users. Many existing affective computing systems make use of sensors that are inflexible and often physically attached to supporting computers. In contrast, HandWave allows an additional degree of flexibility by providing ad-hoc wireless networking capabilities to a wide variety of Bluetooth devices as well as adaptive biosignal amplification. As a consequence, HandWave is used in a variety of affective computing applications such as games, tutoring systems, experimental data collection, and augmented journaling. This paper describes the novel design attributes of this handheld sensor, its development, and various form factors. Future work includes an extension of this approach to other biometric signals of interest to affective computing researchers.

Environment expression is about going beyond the usual Human emotion expression channels in virtual worlds. This work proposes an integrated storytelling model – the – capable of expressing emotions through three channels: cinematography, illumination and music. Stories are organized into prioritized which can be characters or dialogues. Characters synthesize cognitive emotions based on the OCC emotion theory. Dialogues have collective emotional states which reflect the participant’s emotional state. During storytelling, at each instant, the highest prioritypoint of interest is focused through the expression channels. The cinematography channel and the illumination channel reflect the point of interest’s strongest emotion type and intensity. The music channel reflectsthe valence of the point of interest’s mood. Finally, a study was conducted to evaluate the model. Results confirm the influence of environment expression on emotion perception and reveal moderate success of this work’s approach.

This paper considers affective interactions to achieve empathic engagement with synthetic characters in virtual learning environments, in order to support and induce the expression of empathy in children. The paper presents FearNot!, a school based virtual learning environment, populated by synthetic characters used for personal, social and health education, specifically bullying issues in schools. An empirical study of 345 children aged 8-11 years who interacted with FearNot! is outlined. The results identify that affective interactions resulting in the expression of empathy were increased when children had high levels of belief and interest in character conversations and if they believed that their interactions had an impact on the characters’ behaviour.