Audio Equalization Gain Tuning for Low-Frequency Error Reduction
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Solution Overview
Problem
Existing equalization technologies for sound signals often result in significant gain errors, particularly in low-frequency bands, due to the fixed delay time and sampling points in signal processing, leading to inefficient manual corrections that are time-consuming and prone to misjudgment.
Innovation Solution
An adjusting system and method that self-determine suitable equalization gains for each frequency band by using a processing device with modules for target gain determination, frequency response analysis, and filtering processing, minimizing gain errors by optimizing equalization gains based on frequency band energies and filtering responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If fixed delay time and sampling points are used in signal processing, then device complexity is reduced, but manufacturing precision of equalization gain deteriorates
Solution Approach 1:
The system performs preliminary measurement of the actual frequency response of the audio device before equalization processing. By measuring the real frequency response characteristics in advance, the system can compensate for the fixed filter limitations and achieve more precise equalization gain calculation, resolving the contradiction between simple fixed filtering and precise equalization.
Solution Approach 2:
The system uses feedback from the measured frequency response to iteratively optimize the equalization gain. By continuously measuring the actual frequency response and adjusting the equalization parameters based on the measured data, the system achieves high precision equalization despite using fixed delay time and sampling points, thus resolving the precision issue without increasing device complexity.
2Manufacturing precision
If manual correction is used to adjust low-frequency gain errors, then manufacturing precision may be improved, but productivity deteriorates
Solution Approach 1:
The system performs self-measurement and self-correction of frequency response errors. By automatically measuring the actual frequency response and calculating the optimal equalization gain without human intervention, the system achieves both high precision (comparable to manual correction) and high productivity (automated process), resolving the contradiction between precision and speed.
Solution Approach 2:
The system replaces manual mechanical adjustment with automated electronic measurement and calculation. By using electronic frequency response measurement and algorithm-based gain calculation, the system achieves precise equalization adjustment without manual intervention, thereby improving productivity while maintaining or enhancing precision compared to manual methods.
3Device complexity
If transition frequency band length is fixed, then device complexity is reduced, but manufacturing precision of low-frequency equalization deteriorates
Solution Approach 1:
The system performs preliminary measurement of the actual frequency response including the effects of fixed transition bands. By measuring the real frequency response characteristics in advance, the system can compensate for the fixed transition band limitations and achieve accurate low-frequency equalization, resolving the contradiction between simple fixed filter configuration and precise low-frequency equalization.
Data Source
AI summary
An adjusting system and an adjusting method for equalization processing are provided. Frequency band energies of sound receiving signals are obtained. The frequency band energies correspond to different frequency bands, respectively. Target gains corresponding to frequency bands are determined according to the frequency band energies. Frequency responses of filtering processing with respect to a plurality of center frequencies are obtained. Equalization gains corresponding to the frequency bands and having the least gain error are determined. The gain error is related to a difference between the amplitude obtained after the equalization gains are reflected on the frequency responses corresponding to the filtering processing and the target gains. The equalization gains are inputted into the filtering processing according to the corresponding frequency bands. Accordingly, the impact of the filtering processing can be reduced.