Wiener-Hammerstein Audio Processor Simulation

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Solution Overview

Problem

Existing audio processor simulation methods fail to accurately simulate the nonlinear characteristics of audio processors, leading to inadequate sound reproduction, especially when the distortion characteristics of the source and target speakers differ, and are cumbersome for musicians to carry during performances.

Innovation Solution

The use of a Wiener-Hammerstein model, comprising a pre-filter, saturation characteristic curve, and post-filter, to simulate the sound characteristics of audio processors by analyzing frequency responses of high-level and low-level signals, allowing for precise modeling and simulation of nonlinear audio processor circuits.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If frequency response fitting technology is used to simulate speaker sounds, then the simulation can be implemented, but it cannot accurately simulate the distortion sound and nonlinear characteristics of the speaker

Engineering Contradiction:

Improvesimulation accuracy of distortion soundVSAvoidcapability to simulate nonlinear characteristics

Core Design Contradiction:

Measurement precisionVSAdaptability or versatility

Solution Approach 1:

The patent transforms the simulation approach from linear frequency response fitting to nonlinear parameter modeling using Wiener-Hammerstein models. By changing the mathematical parameters from simple frequency responses to include saturation characteristics and nonlinear transfer functions, the system achieves accurate simulation of distortion sounds and nonlinear speaker characteristics.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces the traditional mechanical/audio signal processing approach with a mathematical modeling approach. Instead of using physical speaker measurements alone, it substitutes a computational Wiener-Hammerstein model that mathematically represents the nonlinear behavior, enabling accurate simulation without requiring physical presence of the original speaker.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If multiple audio processors are purchased to achieve different sound effects, then the sound quality and variety are improved, but the cost and portability deteriorate

Engineering Contradiction:

Improvevariety of sound effectsVSAvoidportability

Core Design Contradiction:

Adaptability or versatilityVSWeight of moving object

Solution Approach 1:

The patent creates a universal audio processing system that can simulate multiple different speaker characteristics and sound effects through a single device. The Wiener-Hammerstein model framework is general enough to represent various nonlinear audio processors, allowing one device to perform the function of multiple specialized audio processors, thereby improving portability while maintaining versatility.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent creates virtual copies of different speaker characteristics through mathematical modeling. Instead of physically carrying multiple original speakers, the system creates accurate computational copies of their nonlinear behaviors using Wiener-Hammerstein models, allowing musicians to access various sound effects from a single portable device.

Inventive Principle:

Principle #26Copying

3Measurement precision

If neural network models are used to simulate nonlinear systems, then the simulation capability is improved, but the computational complexity and CPU requirements increase

Engineering Contradiction:

Improvenonlinear simulation capabilityVSAvoidCPU computational requirements

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The patent changes the mathematical parameters and model structure from complex neural networks to the more efficient Wiener-Hammerstein model. This parameter transformation maintains the ability to represent nonlinear characteristics while significantly reducing computational complexity, making the system suitable for real-time audio processing with lower CPU requirements.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent extracts only the essential nonlinear characteristics needed for audio simulation from the complex neural network approach. By identifying and isolating the key parameters (saturation characteristics, frequency responses) that define speaker behavior, the system achieves accurate simulation without the excessive computational overhead of full neural networks.

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS11297430B2Terminal device, apparatus and method for simulating the characteristic of an audio processor, and computer-readable storage medium

Publication Date: 2022.04.05 SHENZHEN MOOER AUDIO CO LTD

AI summary

The present disclosure provides a method and an apparatus for simulating the sound characteristics of the audio processor, a terminal device and a storage medium. The method simulates the sound characteristic of a target audio processor by constructing a nonlinear model. The nonlinear model consists of a pre-filter, a saturation characteristic curve, and a post-filter. A high-level signal is sent to the target sound processor, and the target sound processor correspondingly sends out the first output signal, and then the first output signal is filtered and performed spectrum analysis to acquire the frequency response of the post-filter; And a low-level signal is sent to the target sound processor, and the target sound processor correspondingly sends out the second output signal, and then the second output signal is filtered and performed spectrum analysis to obtain a frequency response product of the pre-filter and the post-filter.