Video Audio Extraction for Diverse Independent Playback
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Solution Overview
Problem
Conventional video technologies limit video display to visual content only, lacking diversity and providing poor user experience.
Innovation Solution
A method and apparatus for extracting audio from videos based on audio features, storing it in an audio resource pool, and playing it independently, utilizing historical user behavior data for personalized audio recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If video is displayed only as visual content, then the display system is simple, but the user experience is poor and display diversity is limited
Solution Approach 1:
The patent segments the video into independent audio and visual components, allowing the audio to be extracted and displayed separately. This segmentation enables diverse display modes (audio-only, video-only, or combined) without requiring a completely new system architecture, thus improving display diversity while controlling system complexity.
Solution Approach 2:
The patent extracts the audio component from the video stream and stores it in an audio resource pool. This extraction allows the audio to be reused independently for different display purposes, enabling features like audio-only playback, audio searching, and personalized audio recommendations without complicating the overall system.
2Adaptability or versatility
If audio is extracted and stored in an audio resource pool, then audio playback versatility is improved, but the processing time and storage requirements increase
Solution Approach 1:
The patent performs audio extraction and storage in advance during video processing, so that when audio playback is needed, the audio is already ready in the audio resource pool. This preliminary action eliminates the need for real-time audio extraction, significantly reducing processing time and enabling fast, versatile audio playback.
3Ease of operation
If personalized audio recommendations are implemented using historical behavior data, then user experience is improved, but the system complexity and data processing requirements increase
Solution Approach 1:
The system automatically analyzes historical user behavior data and generates personalized audio recommendations without requiring manual input or complex user interaction. The system serves itself by using existing data to automatically adapt content recommendations, improving user experience while keeping the interface simple and the system manageable.
Data Source
AI summary
This application provides techniques of generating an audio resource pool based on extracting audio from target videos. The techniques comprise obtaining target videos; determining at least one to-be-processed video from the target videos based on audio features of the target videos; extracting audio from the at least one to-be-processed video; and generating an audio resource pool based on the extracted audio.