Context-Aware Digital Object Updates in Multi-User Conferences
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Solution Overview
Problem
Existing multi-user conference systems fail to automatically adapt digital objects such as display names, backgrounds, and environments to match the thematic context of a conference, leading to inconsistent and user-manual dependent experiences.
Innovation Solution
A computer-implemented method and system that identifies the thematic context of a multi-user conference using keywords, user associations, and calendar events, and modifies digital objects like backgrounds, display names, and audio using generative AI to align with the context, transmitting these changes to participating devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If digital objects are manually updated by users to match conference context, then user control and customization are maintained, but user burden and time consumption increase
Solution Approach 1:
The system automatically detects conference context through keywords, user associations, and calendar events, then autonomously updates digital objects without requiring manual user intervention. The system serves itself by programmatically identifying context and modifying appropriate digital objects to match the detected theme.
Solution Approach 2:
The system pre-configures multiple digital objects associated with different contexts before the conference begins. When context is detected, the system quickly switches between pre-prepared digital objects rather than creating them in real-time, reducing update time while maintaining customization.
2Adaptability or versatility
If digital objects are automatically updated to match conference context, then user experience and immersion are enhanced, but system complexity increases
Solution Approach 1:
The system segments digital objects into context-specific categories (display names, backgrounds, avatars, environments) and associates each with particular conference themes. This modular organization allows selective updating of only relevant digital objects based on detected context, managing complexity through structured classification.
Solution Approach 2:
The system introduces a context detection module that acts as an intermediary between the conference platform and digital object library. This mediator detects contextual cues from multiple sources (keywords, calendar events, user associations) and translates them into appropriate digital object selections, simplifying the overall system architecture.
3Adaptability or versatility
If multiple digital objects are updated simultaneously to align with thematic context, then immersion and user experience improve, but processing time and computational resources increase
Solution Approach 1:
The system dynamically determines which digital objects to update based on the detected conference context. Rather than updating all digital objects uniformly, the system selectively modifies only those relevant to the current context, optimizing processing efficiency while maintaining immersive experience.
Solution Approach 2:
The system pre-associates digital objects with contextual metadata and organizes them in advance. When context detection occurs, the system quickly retrieves and applies the appropriate pre-configured digital objects rather than generating or searching for them in real-time, significantly reducing processing time.
Data Source
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AI summary
A computer-implemented method for programmatically updating contexts for multi-user conferences may include (i) identifying a multi-user conference being participated in by a plurality of computing devices, (ii) detecting a thematic context of the multi-user conference, (iii) modifying, in response to detecting the thematic context, a digital object within the multi-user conference to align with the thematic context, and (iv) transmitting the modified digital object to the plurality of computing devices as part of the multi-user conference. Various other methods, systems, and computer-readable media are also disclosed.