Acoustic Echo Cancellation Auto-Tuning via Gain Control
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Solution Overview
Problem
Existing acoustic echo cancellers require manual platform-specific tuning for optimal performance across various environments, which is inefficient and challenging to achieve full duplex voice communication with sufficient echo cancellation.
Innovation Solution
A threshold control system dynamically adjusts the non-linear processor's threshold based on the stability of the adaptive filter, allowing the communication device to switch between full-duplex, partial-duplex, and half-duplex modes, and a gain control system adjusts signal attenuation to prevent adaptive filter saturation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual platform-specific tuning is performed for echo canceller, then echo cancellation performance is improved, but device complexity and time consumption increase
Solution Approach 1:
The echo canceller automatically detects platform-specific acoustic characteristics and adapts its parameters without manual intervention. The system performs self-tuning by analyzing the acoustic environment and adjusting filter coefficients dynamically, eliminating the need for manual platform-specific configuration while maintaining optimal echo cancellation performance.
Solution Approach 2:
The system dynamically changes operational parameters such as filter coefficients, adaptation rates, and processing thresholds based on detected acoustic characteristics. By automatically adjusting these parameters according to the specific platform and environment, the system achieves optimal performance across diverse platforms without requiring manual tuning for each configuration.
2Measurement precision
If adaptive filter continuously models echo path, then echo estimation accuracy is improved, but risk of filter saturation increases
Solution Approach 1:
The system implements feedback mechanisms that continuously monitor the adaptive filter's operation and detect signs of saturation. When saturation is detected, the feedback loop adjusts the adaptation rate or resets filter coefficients to prevent saturation while maintaining accurate echo path modeling. This balanced approach ensures both high estimation accuracy and filter stability.
Solution Approach 2:
The adaptive filter operates with dynamic parameters that adjust based on signal conditions. The system varies the adaptation rate, filter order, and other parameters in real-time to optimize performance while preventing saturation. This dynamic operation allows the filter to maintain high accuracy in changing acoustic environments without becoming unstable or saturated.
3Reliability
If non-linear processor removes residual echo, then echo cancellation performance is improved, but signal distortion increases
Solution Approach 1:
The non-linear processor applies different processing thresholds and techniques to different portions of the signal spectrum and time domains. By selectively applying echo removal only where residual echo is detected and adjusting the processing intensity locally, the system effectively removes echo while minimizing distortion to legitimate speech signals. This localized processing approach preserves signal quality while achieving superior echo cancellation.
Data Source
AI summary
A gain control system for dynamically tuning an echo canceller, the echo canceller being configured to estimate an echo of a far-end signal and subtract that echo estimate from a microphone signal to output an echo cancelled signal, the gain control system comprising a monitoring unit configured to estimate an energy associated with an impulse response of an adaptive filter configured to generate the echo estimate from the far-end signal and a gain tuner configured to adjust an attenuation of at least one of the microphone signal and the far-end signal in dependence on the estimated energy.