Audio Content Overlap Characterization via Fingerprinting
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Solution Overview
Problem
Current methods for identifying audio content within broadcasts are inadequate for accurately determining the length and presence of copyrighted excerpts, especially in environments with high noise and distortion, and lack effective solutions for royalty collection and content ownership verification.
Innovation Solution
A method that determines content features from audio recordings, identifies matching pairs, and calculates time offsets to accurately determine the extent and duration of overlapping audio segments, even in imperfect copies, using techniques like fingerprinting and statistical moment analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If audio content identification is performed in noisy and distorted broadcast environments, then the ability to detect copyrighted excerpts is improved, but measurement precision deteriorates
Solution Approach 1:
The audio signal is divided into multiple segments or frames, and content identification is performed on each segment independently. This segmentation allows the system to handle noisy environments by analyzing manageable portions of audio rather than attempting to process entire broadcasts at once, thereby maintaining measurement precision despite environmental challenges.
Solution Approach 2:
The patent employs intermediary processing steps including signal filtering, noise reduction algorithms, and intermediate feature extraction between the noisy audio input and final content identification. These intermediary processes clean and prepare the signal, preserving measurement precision even when detecting content in difficult acoustic environments.
2Ease of operation
If traditional file-naming methods are used to organize digital content, then ease of operation is improved, but reliability deteriorates
Solution Approach 1:
The patent replaces manual file-naming mechanisms with automated acoustic fingerprinting and content-based identification systems. Instead of relying on human-operated file naming and editing, the system automatically identifies and organizes content based on its acoustic properties, thereby maintaining ease of operation while dramatically improving reliability and accuracy of content identification.
3Adaptability or versatility
If content identification systems are made more complex to handle various audio formats and conditions, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent implements a universal content identification system that handles multiple audio formats, compression algorithms, and broadcast conditions through a single integrated platform. The system uses format-agnostic acoustic feature extraction and universal fingerprinting techniques that work across MP3, streaming audio, radio broadcasts, and other formats, achieving high adaptability without proportionally increasing system complexity.
Data Source
AI summary
A method of characterizing the overlap of two media segments is provided. In an instance where there is some amount of overlap of a file and a data sample, the file could be an excerpt of an original file and begin and end within the data sample. By matching identified features of the file with identified features of the data sample, a beginning and ending time of a portion of the file that is within the data sample can be determined. Using these times, a length of the file within the data sample can also be determined.