Bi-magnitude Filtering for Nonlinear Echo Cancellation
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Solution Overview
Problem
Conventional acoustic echo cancellation methods are ineffective for mobile devices due to the nonlinearity of the echo path, which differs from the linear assumption made for desktop and laptop computers.
Innovation Solution
A bi-magnitude filtering operation is performed, with a first filtering operation using a generic impulse response function when the audio signal magnitude is below a threshold and a second filtering operation involving a nonlinear function when the magnitude exceeds the threshold, both determined to minimize residual signal power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a linear adaptive filter is used for acoustic echo cancellation, then the system is simple and computationally efficient, but it is ineffective for mobile devices with nonlinear echo paths
Solution Approach 1:
The patent divides the echo cancellation process into two distinct segments based on signal magnitude: a first filtering operation for low-magnitude signals and a second filtering operation for high-magnitude signals. This segmentation allows each filter to be optimized for its specific operating range, improving overall effectiveness without requiring a completely complex system redesign.
Solution Approach 2:
The patent implements dynamic switching between different filtering operations based on the magnitude of the audio signal. The system adapts its processing approach in real-time by comparing signal magnitude against a threshold and selecting the appropriate filter, making the system responsive to changing acoustic conditions while maintaining manageable complexity.
2Reliability
If a single filtering operation is used for all signal magnitudes, then the device complexity is low, but the echo cancellation performance degrades for nonlinear echo paths
Solution Approach 1:
The patent applies different filtering characteristics to different signal magnitude ranges. The first filtering operation uses a generic impulse response function optimized for low-magnitude signals, while the second filtering operation employs a nonlinear function optimized for high-magnitude signals. This local optimization ensures each filter performs best in its designated operating range.
Solution Approach 2:
The patent changes the filtering parameters (impulse response function characteristics) based on the signal magnitude parameter. When the signal magnitude exceeds the threshold, the system switches to a different impulse response function with properties suited for nonlinear echo paths, thereby adapting the filter behavior to match the actual acoustic conditions.
3Loss of energy
If no magnitude-based switching is implemented, then the processing is simpler, but the residual signal power increases due to inappropriate filtering
Solution Approach 1:
The patent incorporates a feedback mechanism where the system continuously monitors the magnitude of the audio signal and uses this information to select the appropriate filtering operation. This closed-loop approach ensures that the most suitable filter is always applied, minimizing residual signal power by matching the filter characteristics to the actual signal conditions.
Solution Approach 2:
The system dynamically adjusts its processing approach by switching between filtering operations based on real-time signal magnitude measurements. This dynamic adaptation allows the system to minimize residual power by selecting the optimal filter for current conditions, rather than using a static filtering approach that would be suboptimal across varying signal levels.
Data Source
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AI summary
Techniques of performing acoustic echo cancellation involve providing a bi-magnitude filtering operation that performs a first filtering operation when a magnitude of an incoming audio signal to be output from a loudspeaker is less than a specified threshold and a second filtering operation when the magnitude of the incoming audio signal is greater than the threshold. The first filtering operation may take the form of a convolution between the incoming audio signal and a first impulse response function. The second filtering operation may take the form of a convolution between a nonlinear function of the incoming audio signal and a second impulse response function. For such a convolution, the bi-magnitude filtering operation involves providing, as the incoming audio signal, samples of the incoming audio signal over a specified window of time. The first and second impulse response functions may be determined from an input signal input into a microphone.