Audio Copyright Detection Using Pitch, Tempo, and Key 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 the pitch, tempo, and key of audio files to create processed iterations, comparing them with a digital rights repository to identify matches and determine copyright infringement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing copyright detection systems are used, then simple audio file comparison is possible, but transformative alterations in pitch, tempo, and key cannot be detected
Solution Approach 1:
The system automatically generates multiple processed iterations of the original audio recording by varying pitch, tempo, and key parameters. These transformed versions are then compared against the digital rights repository to detect copyright infringement, enabling the system to identify transformed versions that would otherwise be undetectable using simple audio comparison methods.
Solution Approach 2:
The system performs preliminary processing by creating processed iterations of the original audio recording before comparison. This preliminary transformation step ensures that the audio file is prepared in multiple potential infringing variations, allowing the detection system to proactively identify copyright infringement rather than relying on direct matches only.
2Measurement precision
If manual analysis of audio files is performed, then detailed examination is possible, but time and effort required increase significantly
Solution Approach 1:
The system automatically generates processed iterations and performs comparisons against the digital rights repository without requiring manual intervention. This self-service approach enables thorough analysis of copyright infringement while significantly reducing the time and effort required compared to manual examination methods.
Solution Approach 2:
The system continuously generates processed iterations and compares them against the repository in an automated loop. This continuous automated action maintains constant surveillance for copyright infringement, eliminating the intermittent nature of manual analysis and significantly reducing detection time while maintaining thoroughness.
3Productivity
If automated detection systems are implemented, then detection speed increases, but complexity of the system increases
Solution Approach 1:
The system divides the audio analysis process into distinct segments: generating processed iterations with varied parameters, comparing against the digital rights repository, and determining matches. This segmentation allows each component to be optimized independently, achieving high detection speed while managing system complexity through modular architecture.
Solution Approach 2:
The system uses a universal comparison mechanism that handles multiple types of audio transformations (pitch, tempo, key variations) through a single integrated process. This multi-functionality approach enables fast automated detection across various infringement scenarios without proportionally increasing system complexity, as the same infrastructure handles all detection tasks.
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.