Conversation Emotion Regulation via Score Threshold Intervention
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Solution Overview
Problem
Emotions in conversations can lead to physiological responses that undermine rational arguments and affect interpersonal relationships, potentially resulting in medical conditions or regrets, as existing systems and methods fail to effectively regulate emotions in real-time.
Innovation Solution
A method and system that monitor conversations, calculate emotion scores for each utterance, and intervene when scores exceed a threshold to return the conversation to a constructive path, using a computer program product with an emotion regulation module that includes natural language processing, intervention, and audit modules to assess and adjust responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time emotion monitoring and intervention systems are implemented in conversations, then emotion regulation effectiveness is improved, but system complexity increases
Solution Approach 1:
The system segments the conversation monitoring process into distinct functional modules: an emotion detection module that analyzes utterances in real-time, a threshold comparison module that evaluates emotion scores against predefined limits, and an intervention module that executes regulatory actions. This segmentation allows each component to perform its specific function efficiently, improving overall emotion regulation effectiveness while managing system complexity through modular design
Solution Approach 2:
The patent introduces an intermediary emotion score metric that mediates between raw emotional expressions and regulatory decisions. The system calculates emotion scores as intermediate values that represent the intensity of emotional states, allowing the intervention mechanism to operate on quantified data rather than raw emotions. This intermediary representation simplifies the control logic and improves regulation reliability by providing a clear decision threshold
2Measurement precision
If continuous conversation monitoring is performed to detect emotions, then emotion detection accuracy is improved, but computational resource consumption increases
Solution Approach 1:
The system applies partial monitoring by focusing computational resources on detecting when emotion scores exceed predefined thresholds rather than continuously analyzing every aspect of the conversation. The intervention mechanism activates only when necessary (when threshold violations occur), allowing the system to achieve adequate emotion detection accuracy while significantly reducing computational resource consumption during normal operation
Solution Approach 2:
The monitoring system operates periodically by evaluating emotion scores at discrete time points corresponding to conversation utterances rather than continuously analyzing every moment of the conversation. This periodic evaluation approach maintains emotion detection accuracy by capturing emotional states at relevant intervals while reducing computational load by avoiding constant analysis
Data Source
AI summary
A method for regulating emotions in conversations is disclosed. In one embodiment, such a method includes monitoring a conversation between participants. The method further divides the conversation into a plurality of utterances and calculates an emotion score for each utterance. The method further determines whether an emotion score of an utterance exceeds a threshold. In the event the emotion score exceeds the threshold, the method intervenes in the conversation in an attempt to return the conversation to a more constructive path. In certain embodiments, this intervention may include taking one or more actions that are specifically tailored to returning the conversation to a more constructive path. In other or the same embodiments, responses or reactions of the participants to the actions are audited to determine if the actions were successful in returning the conversation to a more constructive path. A corresponding system and computer program product are also disclosed.