Live Content Adaptation via Reference Emotion Detection
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Solution Overview
Problem
Existing methods for adapting live content based on user emotions are not effectively utilized for live streaming, particularly in providing personalized content experiences that avoid undesirable emotional responses, such as fear or nudity, for target users.
Innovation Solution
A method and system that determine a reference group's emotions and adapt live content, such as video or audio, for target users by modifying the content based on their preferences and emotional indicators, while ensuring a minimum latency in streaming, using a content determiner that associates emotions with specific time sections and adjusts content accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If live content is adapted in real-time based on reference user emotions, then content personalization is improved, but latency increases
Solution Approach 1:
The system pre-determines emotion indicators and content adaptation rules before live content is consumed. Reference users provide emotional feedback in advance, and the content determiner pre-processes this data to establish adaptation guidelines, allowing real-time content modification without waiting for emotional responses during live streaming.
Solution Approach 2:
The content is divided into discrete time sections and emotion indicators, allowing the system to process and adapt specific segments independently. This segmentation enables parallel processing of multiple content sections while maintaining real-time responsiveness, reducing overall latency.
2Adaptability or versatility
If emotion detection is performed on reference users to adapt content for target users, then content relevance is improved, but system complexity increases
Solution Approach 1:
The content determiner acts as an intermediary between reference users and target users. It receives emotional indicators from reference users, processes this information, and generates adaptation instructions for target users, simplifying the overall system architecture by centralizing the adaptation logic.
Solution Approach 2:
The system uses reference users as proxies or copies to represent target users' preferences. By measuring emotional responses from reference users and applying these patterns to target users, the system avoids the complexity of directly monitoring every target user's emotions while maintaining relevant content adaptation.
3Adaptability or versatility
If content adaptation is triggered based on real-time emotion indicators, then user preference alignment is improved, but processing time increases
Solution Approach 1:
The system pre-establishes emotion-indicator-to-content-adaptation mapping rules before live content consumption. When emotion indicators are detected during live streaming, the system quickly matches them against pre-existing rules rather than performing complex real-time analysis, significantly reducing processing time.
Data Source
AI summary
A method for adapting a piece of live content includes determining a reference group including at least one reference content consumer device being associated with a reference user and including a user state device for detecting a user state; determining that the piece of live content is streamed to the content consumer devices of the reference group; obtaining, from at least one of the content consumer devices of the reference group, at least one respective emotion indicator; determining an emotion; determining a target group comprising at least one target content consumer device being associated with a target user; triggering adapting of the piece of live content based on the at least one emotion indicator and a preference; and triggering the adapted content to be delayed.