30 citations · 51 across the 18 of their papers we have counts for
4 papers · 1 filter
Code Drift: Towards Idempotent Neural Audio Codecs
Patrick O'Reilly, Prem Seetharaman, Jiaqi Su +2
Neural codecs have demonstrated strong performance in high-fidelity compression of audio signals at low bitrates. The token-based representations produced by these codecs have prov…
AutoClip: Adaptive Gradient Clipping for Source Separation Networks
Prem Seetharaman, Gordon Wichern, Bryan Pardo +1
Clipping the gradient is a known approach to improving gradient descent, but requires hand selection of a clipping threshold hyperparameter. We present AutoClip, a simple method fo…
Model selection for deep audio source separation via clustering analysis
Alisa Liu, Prem Seetharaman, Bryan Pardo
Audio source separation is the process of separating a mixture (e.g. a pop band recording) into isolated sounds from individual sources (e.g. just the lead vocals). Deep learning m…
Simultaneous Separation and Transcription of Mixtures with Multiple Polyphonic and Percussive Instruments
Ethan Manilow, Prem Seetharaman, Bryan Pardo
We present a single deep learning architecture that can both separate an audio recording of a musical mixture into constituent single-instrument recordings and transcribe these ins…