Semi-blind multichannel demixing for acoustic echo cancellation
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Solution Overview
Problem
Multimedia devices face challenges in accurately processing audio signals due to acoustic echo interference from their playback systems, which affects automatic speech recognition and hands-free system control.
Innovation Solution
A system and method for multichannel audio signal processing that uses semi-blind multichannel demixing, involving a subband analysis filter bank, single-double talk estimator, subband semi-blind source separation module, and spectral filter bank to decompose and remove echo components from near-end source signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If acoustic echo cancellation is performed using traditional methods, then echo suppression is achieved, but speech recognition accuracy deteriorates due to residual echo and audio artifacts
Solution Approach 1:
The audio signal is segmented into multiple frequency subbands using a filter bank, allowing independent processing of different frequency components. This segmentation enables targeted echo cancellation in each subband while preserving speech components, thereby reducing residual echo without degrading speech recognition accuracy.
Solution Approach 2:
Different processing strategies are applied to different frequency subbands based on local signal characteristics. The system adapts the echo cancellation strength and processing method for each subband, applying stronger cancellation where echo dominates and weaker processing where speech components are present, thus maintaining both echo suppression and speech recognition accuracy.
2Reliability
If multichannel audio processing is used to handle multiple echo sources, then echo cancellation robustness is improved, but computational complexity increases
Solution Approach 1:
The multichannel audio signal is divided into multiple frequency subbands, and echo cancellation is performed independently in each subband. This segmentation reduces the computational burden of processing the entire spectrum simultaneously while maintaining robustness against multiple echo sources through parallel subband processing.
Solution Approach 2:
The system applies echo cancellation selectively in each subband based on the detected echo dominance, rather than uniformly across all frequencies. This partial action approach reduces unnecessary computational operations in subbands where echo is not dominant, lowering overall complexity while maintaining reliability where needed.
3Object-affected harmful factors
If aggressive echo suppression is applied, then echo artifacts are reduced, but speech distortion increases affecting hands-free control
Solution Approach 1:
The system applies different levels of echo suppression to different frequency subbands based on local signal analysis. In subbands where echo is dominant, stronger suppression is applied to reduce artifacts, while in subbands containing speech components, weaker processing preserves speech fidelity, thus balancing artifact reduction with speech quality.
Solution Approach 2:
The system continuously monitors the processed audio signal and adjusts the echo cancellation parameters based on feedback from speech activity detection and echo estimation. This feedback mechanism prevents excessive suppression that would distort speech, maintaining high speech fidelity while still reducing echo artifacts.
Data Source
AI summary
A method for echo cancellation in multichannel audio signals includes receiving a plurality of time-domain signals, including multichannel audio signals and at least one reference signal, transforming the time-domain signals to K under-sampled complex-valued subband signals using an analysis filter bank. A probability of acoustic echo dominance is produced using a single-double talk estimator, and a multichannel source separation is performed based on the probability to decompose the audio signals into a near-end source signal and a residual echoes using source separation. The residual echo components are removed from the near-end source signal using a spectral filter bank, and the subband audio signals are reconstructed to a multichannel time-domain audio signal using a subband synthesis filter.