Streaming Video Content Personalization via Audio-Visual Element Filtering
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Solution Overview
Problem
Users face disturbances from specific sounds and images in streaming video content, such as animal sounds or violent scenes, which can cause distress or discomfort, and existing technologies do not effectively allow for personalized customization of these elements.
Innovation Solution
A system that includes a user interaction module to receive input for managing specific sounds and images, a recognition module to identify these elements using spectral analysis, machine learning, and deep learning techniques, and a modification module to provide a managed version of the content by altering or removing the identified elements, allowing users to customize their viewing experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If streaming video content is provided with full audio and visual elements, then content completeness and quality are improved, but user discomfort and disturbance increase for sensitive users
Solution Approach 1:
The system extracts and removes specific problematic audio elements (animal sounds, loud noises) and visual elements (violence, gore, guns) from the video content based on user preferences, while preserving the rest of the content intact. This allows the content to remain complete overall while removing only the harmful portions that cause user disturbance.
Solution Approach 2:
The system applies different quality treatments to different portions of the content. Instead of uniformly modifying the entire video, it selectively identifies and modifies only the specific segments containing problematic elements (e.g., animal sounds, violent scenes) while leaving other segments unchanged, thus maintaining local quality where needed.
2Device complexity
If generic video content is provided without customization, then system simplicity is maintained, but user personalization and comfort are reduced
Solution Approach 1:
The system dynamically adapts the video content based on real-time user inputs and preferences. Users can adjust their sensitivity thresholds and select which types of content elements to filter, and the system dynamically modifies the playback accordingly. This allows the same system to serve multiple user preferences without requiring separate systems for each user type.
Solution Approach 2:
The system incorporates user feedback mechanisms where users can indicate their comfort levels and preferences regarding different content elements. The system uses this feedback to adjust the filtering and modification parameters, creating a closed-loop system that continuously adapts to user needs while maintaining operational simplicity.
3Productivity
If automated recognition of content elements is implemented, then manual review effort is reduced, but recognition accuracy and precision may be compromised
Solution Approach 1:
The system uses automated recognition algorithms as an intermediary to identify and flag potential problematic content elements. These algorithms scan the video content and generate a list of candidate segments that may contain animal sounds, loud noises, violence, or other sensitive elements. This intermediary step enables rapid processing of large volumes of content while maintaining the option for subsequent verification or adjustment.
Data Source
AI summary
A system for managing audio and visual content in streaming video content includes a user interaction module configured to receive a user input to manage specific types of sounds and images in the streaming video content, a recognition module configured to recognize the specific types of sounds and images in the streaming video content based on the user input, and a modification module configured to provide a managed version of the streaming video content, wherein the recognized specific types of sounds and images are managed in the managed version of the streaming video content.