解决多设备语音通话中因采样率偏移导致的回声消除失效问题
Sample Rate Offset Compensated Acoustic Echo Cancellation For Multi-Device Scenarios
- 将多设备回声消除建模为多通道系统，结合卡尔曼滤波与采样率偏移估计
- 在相关和不相关播放信号下均有效抑制滤波器发散，支持单双讲场景
- 对相关信号设备需独立单通道滤波器以加速偏移估计收敛，适合实际多设备部署
多设备场景下的声学回声消除（AEC）因设备间存在采样率偏移（SRO）而面临挑战。SRO会阻碍AEC滤波器收敛，降低性能。为此，本文将多设备AEC视为多通道问题，采用多通道卡尔曼滤波、SRO估计及远端信号重采样方法进行处理。实验表明，在双设备场景中，该系统在仅回声和双讲条件下，对相关与不相关的播放信号均能有效缓解多通道卡尔曼滤波器的发散问题。对于具有相关播放信号的设备，独立的单通道AEC滤波器对确保SRO估计快速收敛至关重要。
原文摘要 · Abstract (English)
Acoustic echo cancellation (AEC) in multi-device scenarios is a challenging problem due to sample rate offset (SRO) between devices. The SRO hinders the convergence of the AEC filter, diminishing its performance. To address this , we approach the multi-device AEC scenario as a multi-channel AEC problem involving a multi-channel Kalman filter, SRO estimation, and resampling of far-end signals. Experiments in a two-device scenario show that our system mitigates the divergence of the multi-channel Kalman filter in the presence of SRO for both correlated and uncorrelated playback signals during echo-only and double-talk. Additionally, for devices with correlated playback signals, an independent single-channel AEC filter is crucial to ensure fast convergence of SRO estimation.
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