Adaptive Echo Cancellation Filter for Voice Recognition
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Solution Overview
Problem
Existing voice-controlled media playback systems face challenges in accurately recognizing voice commands due to acoustic echo cancellation issues, particularly in environments where the voice input is obscured by the audio output from network microphone devices, leading to delayed recognition of wake words and subsequent commands.
Innovation Solution
The implementation of an adaptive echo cancellation process using an impulse response filter that dynamically adjusts its parameters to rapidly converge and minimize echo, allowing for effective filtering of the audio output from network microphone devices, thereby enhancing the signal-to-noise ratio and improving the recognition of voice commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If acoustic echo cancellation is implemented to filter audio output, then voice command recognition accuracy is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary acoustic echo cancellation processing on the audio output before it can interfere with voice command recognition. By pre-filtering the echo from the audio output, the system prepares a cleaner signal environment that improves subsequent voice recognition accuracy without requiring complex real-time processing during voice input
Solution Approach 2:
An adaptive filter acts as an intermediary between the audio output and the voice recognition system. This filter mediates by selectively removing echo components from the audio signal while preserving other useful audio information, thereby improving voice command detection without directly modifying the core voice recognition algorithm
2Measurement precision
If adaptive filtering is used to minimize echo, then signal-to-noise ratio is improved, but processing time increases
Solution Approach 1:
The adaptive filter updates its parameters periodically rather than continuously, adjusting the filter coefficients at regular intervals based on incoming audio data. This periodic update mechanism maintains effective echo cancellation and signal-to-noise ratio improvement while reducing the computational processing time compared to continuous real-time adaptation
Solution Approach 2:
The system applies partial filtering by focusing the adaptive filter's processing efforts only on the specific frequency ranges and time windows where echo is most prominent. Rather than processing the entire audio signal uniformly, the filter concentrates computational resources on the most critical echo components, achieving adequate signal-to-noise ratio improvement with reduced overall processing time
Data Source
AI summary
Systems and methods for improved acoustic echo cancellation and convergence state detection are disclosed. An adaptive filter of a network microphone device (NMD) can be used to generate a filter output to be applied to microphone input signals for echo cancellation. The filter output can be generated using a reference signal corresponding to source audio content played back via transducers of the NMD. The adaptive filter can be updated dynamically over time based at least in part on an adaptation parameter that determines the rate of adaptation. In response to determining that a reset event has occurred, the adaptation parameter can be reset to a default value. Additionally or alternatively, in response to detecting a convergence error, the adaptation parameter can be reset to a default value.