Automated Usage Data Matching for Royalty Calculation
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Solution Overview
Problem
Existing methods fail to efficiently identify and manage usage data from playlist logs to accurately account for the number of performances or reproductions of sound recordings or other works of authorship, making it burdensome to calculate royalties owed to artists and copyright holders.
Innovation Solution
A method and apparatus that processes and identifies copyrightable works by using an automated matching subsystem to compare cleaned and normalized usage data against a repertoire database, utilizing metadata components like artist name, title, album, and sound recording identification code, with preference for stronger matches and additional information extraction to eliminate false positives and determine the best match.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual identification of sound recordings from metadata is used, then accuracy in identifying recordings can be maintained, but the time and labor required increases significantly
Solution Approach 1:
The patent replaces manual mechanical identification processes with an automated computer-based system that uses audio fingerprinting technology. The system automatically extracts acoustic features from audio signals, generates fingerprints, and matches them against a database without human intervention, thereby eliminating the time-consuming manual process while maintaining or improving identification accuracy through consistent algorithmic application.
Solution Approach 2:
The patent introduces an intermediary audio fingerprint as a mediator between the raw audio signal and the identification result. The fingerprint serves as a compact representation that captures essential acoustic characteristics, enabling efficient comparison and matching against the database while preserving the ability to accurately identify the underlying sound recording.
2Productivity
If automated matching systems are implemented, then processing speed and efficiency improve, but the complexity of the system increases
Solution Approach 1:
The patent segments the identification system into distinct functional modules: audio signal processing, feature extraction, fingerprint generation, database storage, and matching algorithms. Each module performs a specific task and can be independently optimized or replaced, which manages system complexity while enabling high processing efficiency through specialized processing in each segment.
Solution Approach 2:
The patent transforms the audio signal from its original complex time-domain representation into a simplified frequency-domain representation through Fourier transforms and other signal processing operations. This parameter transformation reduces the dimensionality and complexity of the data while preserving the essential identifying characteristics needed for accurate matching.
3Measurement precision
If comprehensive metadata is collected from multiple sources, then identification accuracy improves, but the difficulty of processing and normalizing data increases
Solution Approach 1:
The patent performs preliminary cleaning, normalization, and standardization of metadata from multiple sources before the matching process. This pre-processing step includes resolving inconsistencies in formatting, units, and encoding across different data sources, which simplifies subsequent processing and improves matching accuracy without requiring complex processing during the actual identification operation.
Data Source
AI summary
A management system and method for usage data from usage logs of works of authorship is characterized by the comparison of data components from the usage logs to similar data components for works of authorship stored in a database. The usage data is normalized and cleaned prior to comparison, and additional information from the usage data can be extracted for later use in the comparison. False positive matches are eliminated from the comparison so that incompatible potential candidate matches are eliminated. In addition, the best match from a group of multiple matches is determined for a particular work from a usage log.