Emotion Recognition System for Real-Time Session Feedback
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Solution Overview
Problem
In voice-based call centers, conference calls, and remote training systems, it is challenging to directly gauge the emotional state of participants without explicit verbal feedback, hindering real-time adjustments to presentations and automated system responses to emotional cues like frustration or urgency.
Innovation Solution
A method that analyzes audio and video feedback from participants to determine emotional states, generating non-visual representations such as lists or graphs for presenters or agents, enabling real-time adjustments and improved interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If audio and video feedback are analyzed to determine emotional states, then real-time assessment capability is improved, but system complexity increases
Solution Approach 1:
The patent introduces an emotion recognition system as an intermediary component that processes audio and video feedback between the dynamic session system and the presenter. This mediator analyzes demonstrative behaviors (facial expressions, tone of voice, body language) and converts them into actionable emotional state information, resolving the contradiction by adding specialized processing capability without overwhelming the core presentation system
Solution Approach 2:
The system implements a feedback loop where emotional state information is continuously provided back to the presenter in real-time. This feedback mechanism enables the presenter to adjust their presentation based on detected emotions (confusion, agreement, boredom, etc.), improving measurement precision by creating a closed-loop system that monitors and responds to participant states
2Loss of information
If visual feedback from participants is provided to the presenter, then emotional state assessment is improved, but information privacy concerns worsen
Solution Approach 1:
The patent extracts only the essential emotional state information from the audio and video feedback, separating it from the raw visual and auditory data. The emotion recognition system identifies key emotional indicators (confusion, agreement, boredom, frustration) and provides this distilled information to the presenter without requiring access to or transmission of the actual video feeds, thus protecting participant privacy while maintaining information utility
Solution Approach 2:
The emotion recognition system acts as a privacy-protecting intermediary that processes visual and audio data locally and provides only aggregated emotional state summaries to the presenter. This mediator architecture ensures that raw participant video and audio remain confidential while still enabling effective emotional feedback for presentation improvement
Data Source
AI summary
A method of linking recognized emotions to non-visual representations includes receiving at a first location information corresponding to demonstrative behaviors of individuals. The behaviors of the individuals may be analyzed during a dynamic session, in which the information is used to determine emotional states of one or more of the individuals. The information about the emotional state may then be used at the first location to determine an action for improving the dynamic session.