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20182022
most citedNeural Pitch-Shifting and Time-Stretching with Controllable LPCNet

14 citations · 40 across the 12 of their papers we have counts for

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5 papers · 1 filter

eess.AS202114 cited

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…

eess.AS2021

Context-Aware Prosody Correction for Text-Based Speech Editing

Max Morrison, Lucas Rencker, Zeyu Jin +3

Text-based speech editors expedite the process of editing speech recordings by permitting editing via intuitive cut, copy, and paste operations on a speech transcript. A major draw…

eess.AS2020

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…

eess.AS2019

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…

eess.AS2019

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…