A unified benchmark shows DNN-supported Kalman filters for acoustic echo cancellation converge faster and cancel more echo than the classical FDKF, with per-bin methods best preserving near-end speech.
Acoustic Echo Control: An Application of Very-High-Order Adaptive Filters,
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Neural Kalman Filters for Acoustic Echo Cancellation
A unified benchmark shows DNN-supported Kalman filters for acoustic echo cancellation converge faster and cancel more echo than the classical FDKF, with per-bin methods best preserving near-end speech.