@inproceedings{d6af949b026b4f23ac62ccdaf7ba2c05,
title = "Auto-DSP: Learning to Optimize Acoustic Echo Cancellers",
abstract = "Adaptive filtering algorithms are commonplace in signal processing and have wide-ranging applications from single-channel denoising to multi -channel acoustic echo cancellation and adaptive beamforming. Such algorithms typically operate via specialized online, iterative optimization methods and have achieved tremendous success, but require expert knowledge, are slow to develop, and are difficult to customize. In our work, we present a new method to automatically learn adaptive filtering update rules directly from data. To do so, we frame adaptive filtering as a differentiable operator and train a learned optimizer to output a gradient descent-based update rule from data via backpropagation through time. We demonstrate our general approach on an acoustic echo cancellation task (single-talk with noise) and show that we can learn high-performing adaptive filters for a variety of common linear and non-linear mul-tidelayed block frequency domain filter architectures. We also find that our learned update rules exhibit fast convergence, can optimize in the presence of nonlinearities, and are robust to acoustic scene changes despite never encountering any during training.",
keywords = "acoustic echo cancellation, adaptive filtering, adaptive optimization, learning to learn, meta-learning",
author = "Jonah Casebeer and Bryan, {Nicholas J.} and Paris Smaragdis",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2021 ; Conference date: 17-10-2021 Through 20-10-2021",
year = "2021",
doi = "10.1109/WASPAA52581.2021.9632678",
language = "English (US)",
series = "IEEE Workshop on Applications of Signal Processing to Audio and Acoustics",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "291--295",
booktitle = "2021 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2021",
address = "United States",
}