Music Analysis Data Matching Using Whole-Track Checksum Parameters
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Solution Overview
Problem
Existing music piece analysis methods for DJs are burdensome due to lengthy processing times and potential inaccuracies in data comparison, particularly when using power spectrum analysis, fingerprint values, or metadata, which do not reliably match music piece data.
Innovation Solution
A system that generates a checksum parameter from the entirety of the music piece data to ensure accurate and rapid acquisition of analysis data by comparing it with stored parameters, using a music piece analysis data distribution system comprising a computer and a server connected via a network, allowing for efficient data transfer and retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If power spectrum analysis is used to extract index information for music piece comparison, then the comparison accuracy is improved, but the processing time increases significantly
Solution Approach 1:
The patent extracts only the essential duration time parameter from the music piece data, separating it from the complex power spectrum analysis. This extracted parameter is then used for rapid comparison without requiring full spectral decomposition, thus reducing processing time while maintaining identification accuracy.
Solution Approach 2:
The patent divides the music piece identification process into two stages: first, rapid filtering using duration time parameter; second, detailed verification only for matching candidates. This segmentation avoids applying complex analysis to all music pieces, significantly reducing overall processing time.
2Productivity
If fingerprint values are generated from music piece data for server comparison, then the data transmission efficiency is improved, but the generation time increases and accuracy decreases for mixed music pieces
Solution Approach 1:
The patent uses a simple, computationally inexpensive duration time parameter instead of complex fingerprint values. This 'cheap' parameter can be generated instantly and discarded after use, avoiding the time-consuming fingerprint generation process while still enabling effective music piece identification.
3Ease of operation
If editable metadata is used for music piece identification, then the ease of operation is improved, but the reliability of comparison decreases
Solution Approach 1:
The patent uses the inherent duration time property of music pieces, which is automatically determined by the file format and cannot be easily edited or falsified. This self-service approach leverages an immutable characteristic of the music data itself, providing reliable identification without requiring manual metadata entry that could be erroneous.
4Volume of stationary object
If music piece analysis data is stored for only a part of the music piece, then the storage space is reduced, but the usability of the analysis data decreases
Solution Approach 1:
The patent stores analysis data covering the entire duration of each music piece, making the data universally applicable for any playback or analysis purpose. This complete coverage ensures the analysis data can be used for full-track playback, partial playback, looping, and various DJ operations, maximizing versatility.
Data Source
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AI summary
A music piece data comparison device (1) includes: a music piece selector (14) that allows a user to select music piece data; a first parameter generator (15) that generates a first parameter from an entirety of the music piece data selected through the music piece selector (14); a first parameter transmitter (16) that transmits the first parameter generated by the first parameter generator (15) to a server (2) being connected in a manner capable of communication; and a music piece analysis data receiver (17) that receives matched music piece analysis data from the server, in which the server stores the music piece analysis data generated for the music piece data associated with a second parameter generated from the entirety of the music piece data and compares the second parameter with the first parameter to find the music piece analysis data whose second parameter matches the first parameter.