Music Data Processing Device Phase Error Calculation
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Solution Overview
Problem
Existing methods for determining tuning values and chord progressions in music data, such as those using autocorrelation and Fourier transform, face challenges in accurately capturing continuous frequency information needed for precise instrument tuning and chord identification.
Innovation Solution
A music data processing device employing Fast Fourier Transform (FFT) calculations to determine phase errors and normalized phase displacements, which are used to calculate current frequencies and tuning values, and subsequently generate chroma vectors for accurate chord determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If FFT-based phase error calculation is used, then tuning value accuracy is improved, but calculation complexity increases
Solution Approach 1:
The patent segments the frequency analysis into discrete bin numbers from FFT, where each bin represents a specific frequency component. By calculating phase errors for individual bins and aggregating results, the system achieves accurate tuning value determination while managing computational complexity through structured decomposition of the signal spectrum.
Solution Approach 2:
The patent introduces phase error as an intermediary parameter that bridges the raw FFT output and the final tuning value. By computing normalized phase displacements and phase errors as intermediate steps, the system transforms complex spectral data into meaningful tuning information, simplifying the overall calculation process while maintaining high accuracy.
2Measurement precision
If continuous frequency information is extracted through phase error calculation, then chord determination accuracy is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary FFT analysis and phase error calculations on the music data before chord determination. By pre-computing the spectral characteristics and phase relationships, the system prepares continuous frequency information in advance, enabling faster and more accurate chord identification without redundant processing during the actual chord analysis phase.
Solution Approach 2:
The patent transforms the representation of frequency information by calculating normalized phase displacements and phase errors, changing the parameter space from raw FFT magnitudes to phase-based continuous frequency measurements. This parameter transformation enables more precise chord determination while optimizing processing efficiency through mathematically efficient phase calculations.
Data Source
AI summary
A music data processing device includes at least one processor, configured to perform the following: performing calculations of Fast Fourier Transform on input data generated from music data inputted for respective processing units; and for each of bin numbers corresponding to respective calculation points of the Fast Fourier Transform, calculating and outputting a shift amount, as a phase error, that is obtained by subtracting, from a phase in a current processing unit obtained from the Fast Fourier Transform calculations, a sum of a phase in a previous processing unit obtained from the Fast Fourier Transform calculations and a normalized phase displacement, wherein the normalized phase displacement is a change in phase that is supposed to occur when the processing unit advances one unit with a bin number frequency corresponding to the bin number.