38 citations · 90 across the 14 of their papers we have counts for
10 papers · 1 filter
Scaling Up Adaptive Filter Optimizers
Jonah Casebeer, Nicholas J. Bryan, Paris Smaragdis
We introduce a new online adaptive filtering method called supervised multi-step adaptive filters (SMS-AF). Our method uses neural networks to control or optimize linear multi-dela…
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…
Style Transfer of Audio Effects with Differentiable Signal Processing
Christian J. Steinmetz, Nicholas J. Bryan, Joshua D. Reiss
We present a framework that can impose the audio effects and production style from one recording to another by example with the goal of simplifying the audio production process. We…
Meta-AF: Meta-Learning for Adaptive Filters
Jonah Casebeer, Nicholas J. Bryan, Paris Smaragdis
Adaptive filtering algorithms are pervasive throughout signal processing and have had a material impact on a wide variety of domains including audio processing, telecommunications,…
Who calls the shots? Rethinking Few-Shot Learning for Audio
Yu Wang, Nicholas J. Bryan, Justin Salamon +2
Few-shot learning aims to train models that can recognize novel classes given just a handful of labeled examples, known as the support set. While the field has seen notable advance…
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…
Metric Learning vs Classification for Disentangled Music Representation Learning
Jongpil Lee, Nicholas J. Bryan, Justin Salamon +2
Deep representation learning offers a powerful paradigm for mapping input data onto an organized embedding space and is useful for many music information retrieval tasks. Two centr…
Few-Shot Drum Transcription in Polyphonic Music
Yu Wang, Justin Salamon, Mark Cartwright +2
Data-driven approaches to automatic drum transcription (ADT) are often limited to a predefined, small vocabulary of percussion instrument classes. Such models cannot recognize out-…
Scene-Aware Audio Rendering via Deep Acoustic Analysis
Zhenyu Tang, Nicholas J. Bryan, Dingzeyu Li +2
We present a new method to capture the acoustic characteristics of real-world rooms using commodity devices, and use the captured characteristics to generate similar sounding sourc…
Impulse Response Data Augmentation and Deep Neural Networks for Blind Room Acoustic Parameter Estimation
Nicholas J. Bryan
The reverberation time (T60) and the direct-to-reverberant ratio (DRR) are commonly used to characterize room acoustic environments. Both parameters can be measured from an acousti…