38 citations · 90 across the 14 of their papers we have counts for
7 papers · 1 filter
Emotion Embedding Spaces for Matching Music to Stories
Minz Won, Justin Salamon, Nicholas J. Bryan +2
Content creators often use music to enhance their stories, as it can be a powerful tool to convey emotion. In this paper, our goal is to help creators find music to match the emoti…
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…
Neural Pitch-Shifting and Time-Stretching with Controllable LPCNet
Max Morrison, Zeyu Jin, Nicholas J. Bryan +2
Modifying the pitch and timing of an audio signal are fundamental audio editing operations with applications in speech manipulation, audio-visual synchronization, and singing voice…
Don't Separate, Learn to Remix: End-to-End Neural Remixing with Joint Optimization
Haici Yang, Shivani Firodiya, Nicholas J. Bryan +1
The task of manipulating the level and/or effects of individual instruments to recompose a mixture of recordings, or remixing, is common across a variety of applications such as mu…
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…