Automatic Hand Raise Management in Virtual Meetings
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Solution Overview
Problem
Participants in virtual meetings often forget to lower their participant indication requests, such as raised hands, leading to unnecessary interruptions and distractions, as the system lacks automatic control to manage these requests based on changing meeting contexts and participant interactions.
Innovation Solution
The technology automatically updates participant indication requests by using meeting states and conversational models to determine contexts, with a context determiner identifying cues from video, audio, and acoustic data to manage participant indication requests, such as raising or lowering hands, through a participant indication controller, ensuring synchronized interactions during virtual meetings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If participants manually manage their own participant indication requests (raised hands), then they have full control over when to raise and lower hands, but they often forget to lower hands leading to unnecessary interruptions and distractions
Solution Approach 1:
The system automatically manages participant indication requests by detecting meeting contexts and participant actions through video/audio analysis, eliminating the need for manual hand-lowering while maintaining accurate synchronization with meeting flow. The virtual assistant monitors the meeting and autonomously updates raised hand indicators based on detected speaker changes and context transitions.
2Productivity
If the system automatically controls participant indication requests based on meeting context, then unnecessary interruptions are reduced, but the system complexity increases due to context determination requirements
Solution Approach 1:
A virtual assistant acts as an intermediary between meeting participants and the automated control system. The virtual assistant receives meeting data, determines context through analysis of video/audio content, and controls participant indication requests based on detected meeting states, thereby managing system complexity while maintaining productivity benefits.
Solution Approach 2:
The system continuously monitors meeting data including video and audio inputs to detect speaker changes and context transitions. This feedback loop enables the system to dynamically adjust participant indication requests in real-time, ensuring synchronization with actual meeting flow without requiring pre-programmed complex decision logic.
3Reliability
If the system uses video and audio data to determine meeting context, then participant indication requests are synchronized with meeting progression, but the use of energy and processing power increases
Solution Approach 1:
The system analyzes only the necessary portions of video and audio data required for context determination, such as detecting speaker presence and meeting state transitions. By processing only relevant segments rather than continuous full-resolution data, the system maintains high synchronization accuracy while reducing overall energy consumption compared to comprehensive continuous analysis.
Data Source
AI summary
Systems and methods are provided for automatically controlling a participant indication request based on a context of a meeting. The controlling of the participant indication request includes automatic lowering of a raised hand. A context determiner determines the context of the meeting based on meeting data including video, audio, background acoustic data, and chat messaging. The context determiner uses a global participant indication model for determining a context that is in commonly used among participants of the meeting. An individual participant indication model captures participant-specific rules of determining a context. A meeting state manager determines a meeting state based on the context. The meeting state includes a host presentation, a participant presentation, a conversation, and a polling. A participant indication controller automatically lowers the raised hand based on a combination of the determined context and the meeting state.