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20182022
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7 papers · 1 filter

cs.SD2022

Meta-Learning for Adaptive Filters with Higher-Order Frequency Dependencies

Junkai Wu, Jonah Casebeer, Nicholas J. Bryan +1

Adaptive filters are applicable to many signal processing tasks including acoustic echo cancellation, beamforming, and more. Adaptive filters are typically controlled using algorit…

cs.SD2021

Auto-DSP: Learning to Optimize Acoustic Echo Cancellers

Jonah Casebeer, Nicholas J. Bryan, Paris Smaragdis

Adaptive filtering algorithms are commonplace in signal processing and have wide-ranging applications from single-channel denoising to multi-channel acoustic echo cancellation and…

cs.SD2021

Sound Event Detection with Adaptive Frequency Selection

Zhepei Wang, Jonah Casebeer, Adam Clemmitt +2

In this work, we present HIDACT, a novel network architecture for adaptive computation for efficiently recognizing acoustic events. We evaluate the model on a sound event detection…

cs.SD2020

Communication-Cost Aware Microphone Selection For Neural Speech Enhancement with Ad-hoc Microphone Arrays

Jonah Casebeer, Jamshed Kaikaus, Paris Smaragdis

In this paper, we present a method for jointly-learning a microphone selection mechanism and a speech enhancement network for multi-channel speech enhancement with an ad-hoc microp…

cs.SD2019

Deep Tensor Factorization for Spatially-Aware Scene Decomposition

Jonah Casebeer, Michael Colomb, Paris Smaragdis

We propose a completely unsupervised method to understand audio scenes observed with random microphone arrangements by decomposing the scene into its constituent sources and their…

cs.SD2018

Multi-View Networks For Multi-Channel Audio Classification

Jonah Casebeer, Zhepei Wang, Paris Smaragdis

In this paper we introduce the idea of multi-view networks for sound classification with multiple sensors. We show how one can build a multi-channel sound recognition model trained…