479 citations · 1.5k across the 53 of their papers we have counts for
6 papers · 1 filter
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…
Differentiable Signal Processing With Black-Box Audio Effects
Marco A. Martínez Ramírez, Oliver Wang, Paris Smaragdis +1
We present a data-driven approach to automate audio signal processing by incorporating stateful third-party, audio effects as layers within a deep neural network. We then train a d…
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…
Separate but Together: Unsupervised Federated Learning for Speech Enhancement from Non-IID Data
Efthymios Tzinis, Jonah Casebeer, Zhepei Wang +1
We propose FEDENHANCE, an unsupervised federated learning (FL) approach for speech enhancement and separation with non-IID distributed data across multiple clients. We simulate a r…
Point Cloud Audio Processing
Krishna Subramani, Paris Smaragdis
Most audio processing pipelines involve transformations that act on fixed-dimensional input representations of audio. For example, when using the Short Time Fourier Transform (STFT…
Compute and memory efficient universal sound source separation
Efthymios Tzinis, Zhepei Wang, Xilin Jiang +1
Recent progress in audio source separation lead by deep learning has enabled many neural network models to provide robust solutions to this fundamental estimation problem. In this…