Detecting Device Proximities via AEC Filter Coefficients
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Solution Overview
Problem
Acoustic echo cancellation (AEC) in devices is hindered by the proximity of the speaker to the microphone, leading to ineffective speech recognition, as the output audio from the primary assistant can overpower the microphone signal of the secondary assistant, reducing the effectiveness of echo cancellation.
Innovation Solution
Implementing adaptive finite impulse response (FIR) filters at both the primary and secondary assistants to dynamically calculate filter coefficients, which analyze the distance and output audio strength to determine if the secondary assistant is positioned far enough to provide effective supplementary microphone capabilities, and providing notifications to adjust the device placement if they are too close.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Volume of moving object
If the secondary assistant is placed close to the primary assistant for compact device arrangement, then device compactness is improved, but acoustic echo cancellation effectiveness deteriorates because the output audio from the primary assistant overpowers the microphone signal of the secondary assistant
Solution Approach 1:
The system continuously monitors the microphone signal at the secondary assistant to detect the presence and strength of output audio from the primary assistant. Based on this feedback, the system dynamically adjusts the operational state of the secondary assistant's microphone, switching between supplemental mode (when output audio is strong) and independent mode (when output audio is weak), thereby maintaining AEC effectiveness despite close physical proximity
Solution Approach 2:
The system dynamically changes the operational characteristics of the secondary assistant's microphone based on real-time acoustic conditions. The microphone transitions between being actively used for speech capture and being deactivated or suppressed, depending on the strength of the output audio from the primary assistant detected in its signal, allowing the device arrangement to adapt to varying acoustic environments
2Reliability
If the secondary assistant is placed far from the primary assistant to improve acoustic echo cancellation, then AEC effectiveness is improved, but device compactness and portability deteriorate
Solution Approach 1:
The system uses feedback from the microphone signal analysis to determine when the secondary assistant should be actively used. By continuously monitoring the ratio of output audio strength to user speech strength, the system can dynamically enable or disable the secondary microphone based on current acoustic conditions, eliminating the need for fixed large spacing
Solution Approach 2:
The system changes the operational parameters of the secondary assistant's microphone based on detected acoustic conditions. When output audio strength exceeds a threshold relative to user speech, the system adjusts the microphone's operational state (deactivating or suppressing it), effectively adapting the system's acoustic parameters to maintain performance in compact configurations
3Power
If the output audio strength from the primary assistant is increased to improve speech output quality, then speech output quality is improved, but the ability to capture user speech at the secondary assistant deteriorates because the output audio overpowers the microphone signal
Solution Approach 1:
The system monitors the microphone signal at the secondary assistant to detect when output audio from the primary assistant becomes too strong. Based on this feedback, the system adjusts the operational state of the secondary microphone, preventing it from capturing overwhelmed signals and maintaining accurate user speech capture
Solution Approach 2:
The system uses the analyzed microphone signal as an intermediary indicator to control the operational state of the secondary microphone. By analyzing the strength ratio between output audio and user speech in the microphone signal, the system mediates between the need for high output audio quality and the need for accurate speech capture
Data Source
AI summary
An audio device may be configured to produce output audio and to capture input audio for speech recognition. In some cases, a second device may also be used to capture input audio to improve isolation of input audio with respect to the output audio. In addition, acoustic echo cancellation (AEC) may be used to remove components of output audio from input signals of the first and second devices. AEC may be implemented by an adaptive filter based on dynamically optimized filter coefficients. The filter coefficients may be analyzed to detect situations in which the first and second devices are too close to each other, and the user may then be prompted to increase the distance between the two devices.