Sample Rate Offset Compensated Acoustic Echo Cancellation For Multi-Device Scenarios

TL;DR

This paper proposes a novel multi-channel acoustic echo cancellation method that compensates for sample rate offset using a Kalman filter, improving convergence and performance in multi-device scenarios.

Contribution

It introduces a multi-channel AEC approach with SRO estimation and resampling, addressing divergence issues caused by sample rate offsets in multi-device environments.

Findings

Mitigates divergence of the Kalman filter with SRO in two-device setups

Effective in both correlated and uncorrelated playback signal scenarios

Highlights importance of single-channel AEC for correlated signals

Abstract

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.