Automated Royalty Tracking via Audio Fingerprinting
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Solution Overview
Problem
Current methods for monetizing public music performances are inefficient and prone to human error, particularly in tracking and managing royalties, as they rely on manual reports and spot-checking, which can lead to inaccuracies and are impractical for the large number of rights owners involved.
Innovation Solution
A system that uses clusters of computing devices with sound sensing mechanisms and wireless transceivers to autonomously detect and adjust audio frequencies and intensities, and a method for managing public music performance royalties through a network of IoT devices, databases, and servers to streamline the process of identifying rights owners and facilitating royalty payments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual reports and spot-checking are used to track royalties, then the process can be implemented with existing infrastructure, but human error increases and measurement precision deteriorates
Solution Approach 1:
The patent replaces manual mechanical processes (paper reports, physical spot-checking) with automated electronic systems including audio fingerprinting technology, digital databases, and algorithmic matching processes. This substitution eliminates human error in tracking while maintaining implementation feasibility through software-based solutions.
Solution Approach 2:
The system enables automated self-service functionality where the royalty tracking system automatically generates reports, performs matching through audio fingerprinting, and identifies rights owners without requiring manual intervention. This self-automating approach improves precision while reducing the operational complexity burden on users.
2Productivity
If automated audio detection systems are deployed, then measurement precision and productivity improve, but device complexity increases
Solution Approach 1:
The patent implements a multi-functional system that combines audio fingerprinting, database searching, rights owner identification, and royalty calculation into a single integrated platform. This universal system handles multiple aspects of royalty collection simultaneously, improving overall productivity while consolidating complexity into one cohesive system rather than multiple separate components.
Solution Approach 2:
The system introduces intermediate components such as audio fingerprint templates and matching algorithms that bridge the gap between raw audio detection and final royalty determination. These intermediaries simplify the overall process by breaking down complex tasks into manageable stages, improving productivity without overwhelming system complexity.
3Reliability
If manual reporting by venue staff is used, then ease of operation is maintained, but reliability and measurement precision worsen
Solution Approach 1:
The system performs self-monitoring through automated audio detection and fingerprinting, eliminating the need for manual reporting by venue staff. The system autonomously tracks performances, generates accurate data, and maintains reliability without requiring human operators, thereby improving both reliability and ease of operation simultaneously.
4Measurement precision
If spot-checking is performed periodically, then some verification is achieved, but time loss increases and productivity decreases
Solution Approach 1:
The system transitions from periodic spot-checking to continuous automated verification through ongoing audio fingerprinting and real-time performance tracking. This continuous operation maintains high measurement precision without time loss, as the verification process occurs continuously in the background rather than requiring dedicated spot-checking intervals.
Data Source
AI summary
Methods and apparatus, including software, for collecting and managing public music performance royalties and royalty payouts are described. On the listeners side, song/audio fingerprint data is collected and transmitted to the rights owner side, where the rights owner side verifies the song/audio fingerprint data, calculates royalty payments, and in some cases, automates the royalty payments. Public music performance royalty payments are based on the song/audio fingerprint data collected by listeners/clients, as well as business logic servers.