DJ Transform Sound Processing for Time-Frequency Resolution
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Solution Overview
Problem
The Short-time Fourier Transform (STFT) faces a limitation in simultaneously improving temporal and frequency resolution due to the Fourier uncertainty principle, leading to difficulties in distinguishing between frequencies and determining the exact time of frequency occurrence in sounds.
Innovation Solution
A sound processing method using the DJ transform, which models the behavior of hair cells with a plurality of springs, each with different natural frequencies, to enhance both temporal and frequency resolution by calculating displacement, velocity, energy, and amplitude, and extracting natural frequencies through a spring modeling unit, frequency extraction unit, and error inspection unit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the window size is increased to improve frequency resolution, then frequency resolution is improved, but temporal resolution decreases
Solution Approach 1:
The invention segments the sound signal processing into multiple overlapping windows with different sizes. By using both long windows (for frequency resolution) and short windows (for temporal resolution) simultaneously, the system overcomes the limitation of single-window-size approaches. The overlapping structure allows continuous monitoring of both frequency and temporal characteristics without being constrained by the Fourier uncertainty principle.
2Loss of time
If the window size is decreased to improve temporal resolution, then temporal resolution is improved, but frequency resolution decreases
Solution Approach 1:
The system divides the signal processing into multiple segments with different window sizes. Short windows are used to capture temporal changes with high resolution, while long windows provide frequency resolution. The overlapping arrangement ensures that both resolutions are maintained simultaneously across the entire signal duration, eliminating the need to choose between the two resolutions.
3Ease of operation
If a rectangular filter is used for simplicity, then ease of operation is improved, but measurement precision of frequency decreases
Solution Approach 1:
The invention changes the filter parameters by using different window functions (such as Hamming, Hanning, or Blackman windows) instead of simple rectangular filters. This parameter change reduces spectral leakage and improves frequency extraction accuracy while maintaining computational efficiency. The system can adaptively select different window functions based on the specific application requirements.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The DJ transform method achieves improved temporal and frequency resolution, enabling accurate sound recognition, synthesis, and error inspection, applicable in fields like speech recognition, speaker verification, and sound-based diagnostics.
Implementation Method 1
A spring modeling unit that calculates displacement and velocity of each of the plurality of springs by modeling a plurality of springs, each of which has a different natural frequency and vibrates according to an input sound
Implementation Method 2
modeling a plurality of springs, each of which has a different natural frequency and vibrates according to an input sound
Data Source
AI summary
According to research findings, it is known that human hearing ability is not restricted by the Fourier uncertainty principle. The present disclosure intends to propose the sound processing method and device using the DJ transform method, a new frequency extraction method from understanding of the human hearing ability that improves the temporal resolution as well as the frequency resolution simultaneously based on the operating principle of hair cells constituting the cochlea.