Biometric Content Identification via Audio Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for discovering and viewing electronic media content on the Internet are inefficient due to reliance on limited and unreliable metadata, leading to incomplete and inaccurate video retrieval, especially for user-generated content, and are resource-intensive for biometric analysis, resulting in users missing desired content and decreased website usage and advertising revenue.
Innovation Solution
A computer-implemented method and system that generates biometric models for individuals, extracts and analyzes image and audio data from electronic media content to calculate the probability of content involvement, and applies this probability to rank and filter content, allowing for effective person-specific search and notification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If biometric analysis is used to identify people in videos, then measurement precision and reliability of content identification are improved, but use of energy and computational resources increase significantly
Solution Approach 1:
The patent segments the video processing task by first extracting only audio data and performing speech-to-text conversion, rather than analyzing the entire video stream including visual content. This segmentation allows biometric identification to be performed on a smaller, more efficient subset of data (audio only), reducing computational resources while maintaining identification accuracy for spoken content
Solution Approach 2:
The patent extracts and analyzes only the audio component from video content, separating it from the visual component. By taking out just the audio data for biometric analysis, the system achieves person identification without the computational overhead of full video analysis, resolving the contradiction between accuracy and resource consumption
2Reliability
If comprehensive biometric analysis of all video content is performed, then reliability of user notifications is improved, but productivity of content retrieval decreases due to resource intensity
Solution Approach 1:
The patent applies partial action by performing biometric analysis only on audio data rather than comprehensive video analysis. This partial approach to content analysis maintains sufficient reliability for person identification through speech while significantly improving content retrieval productivity by reducing computational load
3Ease of operation
If metadata-based video search is used, then ease of operation is improved, but measurement precision and completeness of search results deteriorate
Solution Approach 1:
The patent merges metadata-based search with biometric speech recognition to create a hybrid search system. This combination maintains the ease of operation of metadata search while improving measurement precision by incorporating actual spoken content analysis, allowing users to search by both keywords and person identification
Data Source
AI summary
Systems and methods are disclosed for manipulating electronic multimedia content to a user. One method includes generating a plurality of biometric models, each biometric model corresponding to one of a plurality of people; receiving electronic media content over a network; extracting image or audio data from the electronic media content; detecting biometric information in the image or audio data; and calculating a probability of the electronic media content involving one of the plurality of people, based on the biometric information and the plurality of biometric models.