7.4k citations · 24.2k across the 136 of their papers we have counts for
5 papers · 1 filter
R-MelNet: Reduced Mel-Spectral Modeling for Neural TTS
Kyle Kastner, Aaron Courville
This paper introduces R-MelNet, a two-part autoregressive architecture with a frontend based on the first tier of MelNet and a backend WaveRNN-style audio decoder for neural text-t…
MIDI-DDSP: Detailed Control of Musical Performance via Hierarchical Modeling
Yusong Wu, Ethan Manilow, Yi Deng +6
Musical expression requires control of both what notes are played, and how they are performed. Conventional audio synthesizers provide detailed expressive controls, but at the cost…
NU-GAN: High resolution neural upsampling with GAN
Rithesh Kumar, Kundan Kumar, Vicki Anand +2
In this paper, we propose NU-GAN, a new method for resampling audio from lower to higher sampling rates (upsampling). Audio upsampling is an important problem since productionizing…
Harmonic Recomposition using Conditional Autoregressive Modeling
Kyle Kastner, Rithesh Kumar, Tim Cooijmans +1
We demonstrate a conditional autoregressive pipeline for efficient music recomposition, based on methods presented in van den Oord et al.(2017). Recomposition (Casal & Casey, 2010)…
SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
Soroush Mehri, Kundan Kumar, Ishaan Gulrajani +5
In this paper we propose a novel model for unconditional audio generation based on generating one audio sample at a time. We show that our model, which profits from combining memor…