Conference Session Burst Activity Speaker Association
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Solution Overview
Problem
Conventional conference systems do not effectively correlate reactions occurring during a conference session with the speaker, limiting user engagement and understanding of audience sentiment.
Innovation Solution
A system that detects burst activity by identifying a threshold number of notable events within a time period and associates it with the speaker, communicating data through notifications, visual elements, or transcripts to inform users of strong audience reactions, thereby enhancing user engagement and understanding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional conference systems are used to enable remote communication, then users can participate in conference sessions via remote devices, but the systems cannot correlate reactions during the session with the speaker
Solution Approach 1:
The patent introduces an intermediary system that includes a processor and memory to detect notable events, determine burst activity, and correlate reactions with speakers. This intermediary component processes conference data, audio data, and reaction data to establish the correlation that conventional systems lack, without requiring fundamental changes to the existing conference infrastructure.
Solution Approach 2:
The system implements feedback by detecting reactions from participants and providing information back to users about audience sentiment and burst activity. This feedback loop allows users to understand how their speaking correlates with participant reactions, enabling continuous improvement of communication effectiveness during and after conference sessions.
2Productivity
If the system detects and communicates burst activity data to increase user engagement, then users can understand audience sentiment, but this requires additional processing and communication infrastructure
Solution Approach 1:
The system performs preliminary actions by pre-defining thresholds for notable events and burst activity detection. These thresholds are established in advance to guide the detection process, allowing the system to efficiently identify meaningful patterns without requiring complex real-time analysis of every individual reaction or event during the conference session.
Solution Approach 2:
The system utilizes parameter changes by monitoring variations in reaction frequency and intensity over time. By detecting when reaction parameters exceed predefined thresholds within specific time windows, the system identifies burst activity and correlates it with speakers, transforming raw reaction data into meaningful engagement metrics.
Data Source
AI summary
Described herein is a system configured to determine when burst activity (e.g., an activity hotspot) occurs in a conference session, and to associate the burst activity with a speaker that is speaking at a time when the burst activity occurs. Burst activity occurs when a threshold number of notable events (e.g., five, ten, fifty, one hundred, one thousand, etc.) occur within a threshold time period (e.g., ten seconds, thirty seconds, one minute, etc.). In various examples, the thresholds can be established relative to a number of participants in a conference session and/or a duration of a conference session (e.g., a scheduled duration). The system can then communicate data indicating that a threshold number of events occurred while an individual speaker is speaking.