Personalized Virtual Collaboration Avatars with Context-Aware Body Language
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Solution Overview
Problem
Existing virtual collaboration technologies struggle to effectively simulate face-to-face interactions, as they are limited by technological constraints in sharing certain types of information, leading to inefficiencies in global team collaboration.
Innovation Solution
A computer-implemented method utilizing an IoT sensor set to correlate body language with spoken context, and a generative adversarial network (GAN) to adapt avatars in real-time to personalized virtual collaboration environments, ensuring appropriate body language based on location and preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional virtual collaboration technologies are used, then basic communication is enabled, but face-to-face interaction simulation is insufficient due to technological constraints in sharing contextual information
Solution Approach 1:
The patent creates virtual copies (avatars) of participants that replicate not only visual appearance but also behavioral characteristics, body language, and contextual information. These avatars serve as digital twins that preserve and transmit contextual cues that would otherwise be lost in traditional virtual collaboration, enabling more effective remote interaction by copying the full spectrum of face-to-face communication elements.
2Adaptability or versatility
If generic virtual collaboration environments are used, then accessibility is improved, but personalization and individual needs accommodation are reduced
Solution Approach 1:
The system performs preliminary actions by automatically generating personalized virtual environments and avatars based on participant profiles before collaboration sessions begin. Historical data, preferences, and contextual information are pre-processed to configure tailored environments, eliminating the need for manual setup while delivering personalized experiences. This preliminary configuration reduces on-demand complexity while maintaining high adaptability.
3Measurement precision
If real-time avatar adaptation is implemented, then body language correlation improves, but computational requirements and processing time increase
Solution Approach 1:
The system implements continuous feedback loops where avatar behavior, body language, and environmental interactions are monitored in real-time. This feedback is used to dynamically adjust and refine avatar characteristics during collaboration sessions, improving body language correlation through iterative optimization. The feedback mechanism enables precise measurement and adaptation without requiring excessive computational resources by focusing processing on relevant behavioral parameters.
Data Source
AI summary
In an approach to improve computer-based virtual world collaboration environments, embodiments of the present invention identifies, by a client computer, a structure of a virtual world collaboration room and the placement of participants in the virtual world collaboration room, and correlates, by an internet of things (IoT) sensor set, body language of an avatar to match a spoken context of the avatar. Further, embodiments select personalized virtual world collaboration room or a predetermined physical location to conduct a virtual world collaboration and utilize a generative adversarial network (GAN) to adapt the avatar to the personalized virtual world collaborative environment. Additionally, embodiments perform real-time adaptation, by the GAN, of participating avatars to generate and output a required body language for the participating avatars based on their location different personalized virtual world collaboration rooms.