Meta-AF Demos
Meta-Learning for Adaptive Filters
We release the inputs, targets, and results for five samples in the test set of each adaptive filter task for all models. These samples are all generated using the Meta-AF codebase in this GitHub repo. Please consult our paper for any experimental configuration details as well as descriptions of our baselines.
Acoustic Echo Cancellation
Double-Talk

Near-end | Far-end | Near-end Speech | Speex | LMS | RMSProp | NLMS | RLS | Kalman Filter | Meta-AF |
Double-Talk with Path Change

Near-end | Far-end | Near-end Speech | Speex | LMS | RMSProp | NLMS | RLS | Kalman Filter | Meta-AF |
Double-Talk with Nonlinearities

Near-end | Far-end | Near-end Speech | Speex | LMS | RMSProp | NLMS | RLS | Kalman Filter | Meta-AF |
Equalization
Unconstrained

Target | Input | LMS | RMSProp | NLMS | RLS | Meta-AF |
Constrained

Target | Input | LMS | RMSProp | NLMS | RLS | Meta-AF |
Dereverberation
One, Four, Eight Mic.

Reverberant | Anechoic | NARA 1 Mic. | Meta-AF 1 Mic. | NARA 4 Mic. | Meta-AF 4 Mic. | NARA 8 Mic. | Meta-AF 8 Mic. |
Beamforming
Diffuse Interferer

Clean Speech | Mixture | LMS | RMSProp | NLMS | RLS | Meta-AF |
Directional Interferer

Clean Speech | Mixture | LMS | RMSProp | NLMS | RLS | Meta-AF |