Emotion-Driven Content Modification in Shared HMD Sessions
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Solution Overview
Problem
In shared virtual reality sessions using head-mounted display (HMD) devices, users often experience differing viewing and immersion experiences, leading to disinterest and dropout due to inconsistent emotional engagement with the content.
Innovation Solution
An electronic device modifies media content in real-time based on emotional state information from HMD wearers, using a neural network to select and apply content modification operations such as audio adjustments, subtitle changes, or region masking to maintain optimal emotional states for individual users, while allowing customization and non-linear content navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If content is delivered uniformly to all users in a shared session, then device complexity is reduced and content delivery is simplified, but user engagement deteriorates due to inconsistent emotional experiences
Solution Approach 1:
The patent segments the content delivery system by creating separate content streams for different users based on their emotional states. The server divides a single content source into multiple personalized versions, allowing each user to receive customized content while maintaining overall system simplicity through automated processing.
Solution Approach 2:
The patent applies local quality by customizing content properties (such as audio levels, visual elements, or narrative pacing) specifically for each user based on their detected emotional state, while leaving other content properties unchanged. This allows targeted personalization without requiring complete content redesign.
2Adaptability or versatility
If content is modified in real-time based on emotional state information, then user engagement is improved through personalized experiences, but device complexity increases due to additional processing requirements
Solution Approach 1:
The patent implements feedback by continuously monitoring users' emotional states through sensors and using this information to dynamically adjust content delivery. The emotional state data feeds back into the content modification process, creating a closed-loop system that automatically adapts content without requiring complex manual intervention.
Solution Approach 2:
The system performs self-service by automatically detecting emotional states and selecting appropriate content modifications without human intervention. The server autonomously processes emotional data, determines necessary adjustments, and applies modifications, reducing the need for complex user interfaces or manual content management.
3Adaptability or versatility
If emotional state monitoring is implemented for each user, then content personalization is enhanced, but loss of information increases due to the complexity of processing and interpreting emotional data
Solution Approach 1:
The patent changes parameters by focusing on specific, measurable emotional indicators (such as heart rate, skin conductance, or facial expression metrics) rather than attempting to interpret complete emotional narratives. This selective parameter approach maintains personalization effectiveness while reducing information loss through simplified data processing.
Data Source
AI summary
An electronic device and method are provided for content modification in a shared session among multiple head-mounted display (HMD) devices. The electronic device determines emotional state information associated with a wearer of each of a plurality of HMD devices. Each HMD device renders media content in a computer-simulated environment and the emotional state information corresponds to a first portion of the rendered media content. The electronic device constructs an input feature for a first neural network based on the first portion of the rendered media content and the emotional state information. The electronic device selects, from a set of content modification operations, a first content modification operation based on an application of the first neural network on the input feature. Thereafter, the electronic device modifies the rendered media content based on the selected first content modification operation. The modified media content is rendered on at least one HMD device.