Meeting Relevance Feedback Interface for Off-Topic Detection
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Solution Overview
Problem
Electronic meetings often suffer from off-topic discussions, leading to wasted time, decreased productivity, and reduced participant engagement, as existing technologies lack effective real-time feedback mechanisms to maintain discussion relevance.
Innovation Solution
A method that analyzes audio data from meeting attendees using Automatic Speech Recognition and semantic analysis to determine the semantic distance between the current discussion topic and the meeting topic, providing real-time feedback through visual and auditory notifications to keep discussions on track.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If real-time semantic analysis and feedback mechanisms are added to electronic meeting software, then discussion relevance and productivity are improved, but device complexity and processing requirements increase
Solution Approach 1:
The patent introduces an intermediary semantic analysis system that acts as a mediator between meeting participants and the meeting topic. This system includes a topic model trained on meeting transcripts, a semantic distance calculator, and a feedback generator that translates complex semantic analysis into simple relevance scores and actionable feedback messages, resolving the contradiction by adding intelligence without proportionally increasing perceived complexity
Solution Approach 2:
The patent implements continuous feedback loops where the system monitors discussion content in real-time, calculates semantic distance from the meeting topic, and provides immediate feedback to participants when off-topic discussions are detected. This feedback mechanism maintains productivity by keeping discussions on-track while the system complexity is managed through modular architecture and pre-trained models
2Reliability
If continuous audio processing and semantic analysis are performed during meetings, then discussion relevance is maintained, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary actions by pre-training topic models on historical meeting transcripts and pre-processing audio data into text transcripts before the actual meeting analysis. During the meeting, the system only needs to calculate semantic distance against pre-established topic representations, significantly reducing real-time processing requirements while maintaining reliable topic tracking
Solution Approach 2:
The patent applies partial action by selectively analyzing only portions of the meeting discussion that show significant deviation from the topic rather than continuously processing every word. The system uses threshold-based filtering and only triggers full semantic analysis when relevance scores indicate potential off-topic discussions, reducing overall processing time while maintaining reliability
3Ease of operation
If visual and auditory feedback notifications are provided to attendees, then participant engagement is enhanced, but ease of operation and user experience may deteriorate
Solution Approach 1:
The patent applies local quality by providing targeted feedback to specific participants based on their individual discussion contributions rather than uniform notifications to all attendees. The system identifies which participant is currently speaking or whose transcript segment triggered the off-topic detection, and directs feedback specifically to them, enhancing engagement without creating a chaotic notification environment
Solution Approach 2:
The patent uses transient, lightweight feedback notifications that appear briefly and automatically dismiss themselves after delivering the relevance message. These disposable feedback elements include temporary visual overlays or brief auditory cues that provide immediate guidance without requiring complex interface management or persistent state tracking, maintaining ease of operation while enhancing engagement
Data Source
AI summary
A method, computer system, and a computer program product for discussion relevance feedback associated with an electronic meeting is provided. The method may include determining a meeting topic associated with the electronic meeting and receiving audio data recording the vocal interactions of one or more meeting attendees. The method may further include generating a textual representation of the received audio data and then identifying a current discussion topic based on the generated textual representation. The method may further include determining a semantic distance between the identified current discussion topic and the determined meeting topic and generating discussion relevance feedback based on the determined semantic distance.