Analysis of behaviour patterns of virtual assistants and their cognitive effects

OData support
Dr. Baranyi Péter Zoltán
Department of Telecommunications and Media Informatics

Parallel to the progression virtual and augmented collaborative environments, increasingly important to develop the theoretical and practical background of avatars having the ability of high level of movement, which can improve the effectiveness of its collaboration with the users.

The goal is to extend an existing collaborative virtual environment, with new virtual assistant, with particular attention being paid to the observability and investigate the cognitive effects of its gestures and behavioral patterns on humans. Instead of using analytical methods, the task to develop motion database

based on granular representations of recorded human motion, that may be suitable to generate and test the targeted cognitive impact.

The overall aim to facilitate communication and interaction in virtual collaborative environments, utilizing the cognitive aspects of using gestures and behavioral patterns.

The thesis work has dealt with developing a framework, for exploration of gestures and related behavior patterns of virtual assistants and their cognitive effects in virtual intelligent space.

As a first step, methods were introduced for examination of gestures from a cognitive infocommunicatons (CogInfoCom) point of view.

In this paper gesture types were identified and classified the most practical way, as possible for later recording them in their most naturalistic way, and organizing these behavior patterns into motion database.

An attempt made to collect all the relevant knowledge and latest evidences in gesture studies by the cognitive and related areas of science, indented to preconceive a precise development framework for later exploration of gestures in a virtual- or semi-virtual intelligent space as a cognitive infocommuncation platform.


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