Frequency-Domain Audio Equalizer for Low-CPU Decoding
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Solution Overview
Problem
Conventional audio equalizers in audio and video systems are resource-intensive, often doubling CPU usage and being impractical for real-time systems due to their reliance on time-domain filters, making them expensive and inefficient for consumer market applications.
Innovation Solution
A transform-based audio equalizer that generates equalizer response coefficients directly in the frequency domain, reducing computational effort by avoiding the need for time-domain filters and re-transform processes, and can be integrated into devices or provided as a separate module via various interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional time-domain filters are used for audio equalization, then equalization performance is achieved, but CPU usage doubles and processing efficiency deteriorates
Solution Approach 1:
The patent transforms the equalization operation from time-domain to frequency-domain, changing the fundamental parameter domain. This allows the equalizer to operate on frequency coefficients directly using simple complex multiplication instead of computationally intensive time-domain filtering, thereby maintaining equalization performance while dramatically reducing CPU usage from doubling to only 0.1%-0.2% increase
Solution Approach 2:
The patent replaces the mechanical time-domain filtering approach with a frequency-domain mathematical transformation. Instead of using traditional digital signal processing with time-domain convolution, the system uses frequency-domain multiplication after FFT transformation, substituting a computationally expensive mechanical process with a more efficient mathematical operation
2Reliability
If traditional time-domain equalizers are implemented, then equalization function is provided, but implementation cost becomes too expensive for consumer market
Solution Approach 1:
By changing the operational domain from time to frequency, the patent reduces the computational complexity from O(N²) time-domain convolution to O(N log N) FFT-based frequency-domain multiplication. This parameter transformation makes the equalizer economically viable for consumer market devices with limited processing budgets
3Reliability
If time-domain filters are used, then audio equalization is achieved, but processing complexity and resource requirements increase
Solution Approach 1:
The patent simplifies processing complexity by transforming the equalization operation into the frequency domain where it becomes a simple element-wise multiplication of complex coefficients. This parameter domain change reduces the algorithmic complexity from intensive time-domain filtering to straightforward frequency-domain scaling operations
Solution Approach 2:
The patent performs the computationally intensive FFT transformation once on the input signal, then applies multiple equalization settings by simply changing the frequency coefficients. This preliminary transformation allows rapid switching between different equalization presets without repeating the heavy computation
Data Source
AI summary
An audio equalizer includes an equalization processor that operates in conjunction with a transformed-based audio decoder that generates a decoded audio signal from an encoded audio signal. The equalization processor receives an equalization input signal, generates a plurality of response coefficients in response to the equalization input and applies the response coefficients to partially decoded data of the transformed-based audio decoder.