Adaptive Acoustic Echo Cancellation with Dual-Mode Filters
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Solution Overview
Problem
Acoustic echo cancellation algorithms face challenges in high noise environments, where noise impedes convergence, leading to poor echo cancellation and distortion of speech signals, particularly due to the trade-off between adaptation time and misadjustment in existing adaptive filtering techniques.
Innovation Solution
The adaptive acoustic echo cancellation technique employs multiple filters using different adaptation techniques, such as NLMS and MNLMS algorithms, and converts data into the frequency domain for improved convergence and misadjustment, with a dual-structured architecture for fast and smooth adaptation, and a convergence detector to switch between these modes based on environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single adaptive filtering algorithm is used for echo cancellation, then the algorithm is simple to implement, but it cannot simultaneously achieve fast adaptation and low misadjustment in high noise environments
Solution Approach 1:
The patent divides the echo cancellation system into multiple independent adaptive filtering algorithms, each specialized for specific conditions. One algorithm handles fast adaptation scenarios while another handles low misadjustment scenarios. This segmentation allows each algorithm to be optimized for its specific function without compromising the other, resolving the contradiction between simplicity and reliability.
Solution Approach 2:
The patent implements a dynamic switching mechanism that selects between different adaptive filtering algorithms based on real-time environmental conditions. The system monitors noise levels and convergence characteristics, dynamically switching between algorithms to maintain optimal performance. This dynamic adaptation allows the system to achieve both fast adaptation and low misadjustment by using the appropriate algorithm for each condition.
2Speed
If the adaptation speed is increased to quickly track echo path changes, then the convergence time is reduced, but the misadjustment increases causing distortion in high noise environments
Solution Approach 1:
The patent segments the adaptation process into two distinct modes: fast adaptation mode for quickly tracking echo path changes and precise adaptation mode for minimizing misadjustment. Each mode uses an adaptive filtering algorithm optimized for its specific purpose, allowing the system to achieve both high convergence speed and high accuracy when needed.
Solution Approach 2:
The patent uses a dynamic switching mechanism that transitions between fast adaptation and precise adaptation modes based on real-time conditions. When rapid convergence is needed, the system switches to fast adaptation mode; when precision is critical, it switches to precise adaptation mode. This dynamic behavior resolves the contradiction by making the system adaptable to changing requirements.
3Manufacturing precision
If noise suppression algorithms are applied to preprocess microphone signals, then the signal quality improves, but the echo signal is distorted hindering algorithm convergence
Solution Approach 1:
The patent segments the signal processing pipeline into separate functional blocks: one for noise suppression and another for echo cancellation. By using multiple adaptive filtering algorithms that operate on the original microphone signal without prior noise suppression, the system avoids the distortion problem while still achieving clean output through the combined effect of multiple algorithms.
Solution Approach 2:
The patent converts the harmful effect of noise on convergence into a beneficial feature by using multiple adaptive filtering algorithms with different convergence characteristics. The algorithms are designed to handle noisy conditions inherently, transforming the noise problem into an opportunity to demonstrate the robustness and adaptability of the multi-algorithm approach.
Data Source
AI summary
An acoustic echo cancellation technique. The present adaptive acoustic echo cancellation technique employs a plurality of acoustic echo cancellation filters which use different adaptation techniques which may employ different parameters such as step size, to improve both the adaptation algorithm convergence time and misadjustment over previously known acoustic echo cancellation techniques.