Emotion-Responsive Music Queues for Objective Mood Regulation
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Solution Overview
Problem
Existing media recommendation systems lack an objective framework for labeling and regulating user emotions, leading to subjective categorizations and unreliable emotional feedback, which hampers personalized mood regulation and user connections.
Innovation Solution
A system and method that generates plots of emotional intensity reactions in real-time, verifies emotional thresholds, and recommends media based on these plots to tailor emotional experiences, using both explicit and implicit user feedback to create personalized media queues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If subjective categorization methods are used for media recommendations, then ease of implementation is improved, but measurement precision of user emotions deteriorates
Solution Approach 1:
The patent replaces subjective human categorization (mechanical/manual system) with automated emotion detection technology that analyzes user reactions to media. This substitution enables objective measurement of emotional responses through computational analysis, resolving the contradiction by maintaining ease of implementation while dramatically improving measurement precision through automated systems.
Solution Approach 2:
The system implements feedback loops where user emotional responses to media are continuously measured and used to refine future recommendations. This feedback mechanism allows the system to learn from actual user reactions rather than relying on subjective pre-categorization, improving measurement precision while maintaining automated operation.
2Measurement precision
If automated emotion detection is implemented, then measurement precision of user emotions is improved, but device complexity increases
Solution Approach 1:
The patent applies multi-functionality by using a single integrated system that performs multiple tasks: detecting emotional responses, analyzing reaction patterns, generating personality profiles, and making media recommendations. This universal approach improves measurement precision while managing complexity through consolidation rather than separate specialized systems.
Solution Approach 2:
The system employs self-service mechanisms where user interactions with media automatically generate data for personality profiling without requiring manual input. The system serves itself by using its own operational data to improve its recommendations, reducing the complexity burden of external intervention while maintaining high measurement precision.
3Adaptability or versatility
If personality profiling based on emotional reactions is used, then adaptability to individual users is improved, but loss of information increases due to privacy concerns
Solution Approach 1:
The patent extracts only the essential emotional reaction data needed for personality profiling while leaving out unnecessary personal information. By selectively extracting only the emotional response patterns relevant to media preferences, the system achieves high personalization capability while minimizing privacy intrusion and information loss.
Data Source
AI summary
A system and its corresponding method are provided for recommending media based on emotion-related feedback from a user. In one example of the system and its corresponding method, songs are assigned to a queue according to objective criteria for achieving desired emotions with the user. Songs may also be assigned to the queue based on documented similarities between various user personality profiles.