Multimedia Stream Rendering Using Topic and Emotion Extraction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current video conferencing systems lack multi-dimensional analysis and mining of multimedia data, failing to effectively utilize media data for enhanced business communication experiences.
Innovation Solution
A multimedia data processing method and apparatus that parses audio and video streams to extract text and expression features, matches them with preset mapping relationships to determine topic and emotion data, and renders this information for enhanced multimedia presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If video conferencing systems provide basic video/voice call control and media channel services, then communication functionality is ensured, but multi-dimensional analysis and mining of multimedia data cannot be performed
Solution Approach 1:
The system segments multimedia data processing into distinct modules: audio stream parsing for text features, video stream parsing for expression features, topic feature determination, emotion index determination, and rendering. This modular segmentation enables multi-dimensional analysis while maintaining manageable system complexity through division of labor across specialized processing components.
2Loss of information
If audio and video streams are parsed to extract text and expression features, then multi-dimensional value information is obtained, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary parsing of audio streams to extract text features and preliminary parsing of video streams to extract expression features before main processing. By preparing feature data in advance through preliminary action, the system reduces the computational burden during main processing and minimizes overall processing time while maintaining complete information extraction.
Solution Approach 2:
The system extracts only the essential features needed for analysis: text features from audio streams and expression features from video streams. By taking out only the relevant information rather than processing all raw data, the system achieves complete information extraction for the required dimensions while significantly reducing processing time and computational resource consumption.
3Extent of automation
If text feature data and expression feature data are matched with preset mapping relationships to determine topic and emotion data, then intelligent analysis capability is enhanced, but system complexity increases
Solution Approach 1:
The system performs preliminary matching of text feature data with preset mapping relationships to determine topic feature data, and preliminary matching of expression feature data with preset mapping relationships to determine emotion index data. By performing these matching operations in advance, the system enhances intelligent analysis capability while managing complexity through structured, pre-defined mapping relationships that can be maintained and updated independently.
Data Source
AI summary
A multimedia data processing method and apparatus, and a computer-readable storage medium are disclosed. The method may include: acquiring an audio stream and a video stream of multimedia data; parsing the audio stream to obtain text feature data, and matching the text feature data according to a preset mapping relationship to determine topic feature data; parsing the video stream to obtain expression feature data, and matching the expression feature data according to a preset mapping relationship to determine an emotion index; and rendering the multimedia data based on the text feature data, the emotion index, and the topic feature data.