Music Copyright Detection Using Iterative Audio Variations
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Solution Overview
Problem
Existing systems fail to effectively detect copyright infringement of music by automatically analyzing transformative alterations in pitch, tempo, and key of audio compositions.
Innovation Solution
A system that iteratively varies pitch, tempo, and key of audio files to create processed iterations, comparing them with digital rights repository files for automated infringement detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual analysis of music compositions is used to detect copyright infringement, then detection accuracy can be maintained, but the process is time-consuming and labor-intensive
Solution Approach 1:
The patent replaces manual mechanical analysis with an automated computer-based system that uses audio processing algorithms to detect copyright infringement. The system automatically compares audio files by extracting features and matching patterns, eliminating the need for human analysts to manually review each file while maintaining detection accuracy.
Solution Approach 2:
The system enables self-service detection by allowing the platform to automatically analyze uploaded audio files without requiring manual intervention. The automated comparison engine processes files independently, matching them against existing content in the digital rights repository and generating results without human assistance.
2Productivity
If automated detection systems are implemented, then processing speed increases, but the systems fail to detect transformed infringing content with altered pitch and tempo
Solution Approach 1:
The patent applies parameter changes by systematically varying pitch and tempo of the reference audio file to create multiple transformed versions. The system adjusts these parameters within expected ranges of transformation and compares each variation against uploaded content, enabling detection of infringing material that has been modified through pitch shifting or speed changes.
Solution Approach 2:
The system implements dynamics by creating a flexible, adaptive comparison process that adjusts to different transformation parameters. Rather than using a static comparison method, the system dynamically generates multiple versions of the reference audio with different pitch and tempo characteristics, making the detection process adaptable to various forms of transformation.
3Reliability
If pitch and tempo variations are manually adjusted to detect infringement, then detection capability improves, but the complexity and time required increases significantly
Solution Approach 1:
The patent replaces complex manual adjustment processes with automated computer-based algorithms that systematically vary pitch and tempo parameters. The system uses software to automatically generate transformed versions of audio files and perform comparisons, eliminating the need for manual intervention while managing the complexity through programmed automation.
Solution Approach 2:
The system manages complexity by implementing structured parameter changes within defined ranges. Rather than exploring all possible transformations, the system adjusts pitch and tempo by specific intervals and amounts that are most likely to match infringing content, reducing the computational complexity while maintaining effective detection capability.
Data Source
AI summary
A system to detect an infringing audio composition is disclosed. The system is configured to receive an audio file from a user; prepare track samples based on the audio file to compare with audio files stored with a digital rights repository; determine an original audio recording from the digital rights repository; prepare an acapella version of the original audio recording and/or an instrumental version based on the original audio recording; process, by iteratively varying a pitch, a tempo and/or a key of, the versions to create a processed iteration of each version; automatically compare the processed iterations of the audio files stored with a digital rights repository; determine a match between the processed iterations and the audio files stored with the digital rights repository; and determine a digital rights action to take based on the match between the processed iteration of each of the versions.