1 citations · 1 across the 3 of their papers we have counts for
3 papers
eess.AS2021
Towards Universal Neural Vocoding with a Multi-band Excited WaveNet
Axel Roebel, Frederik Bous
This paper introduces the Multi-Band Excited WaveNet a neural vocoder for speaking and singing voices. It aims to advance the state of the art towards an universal neural vocoder,…
eess.AS2020★ 1 cited
Semi-supervised learning of glottal pulse positions in a neural analysis-synthesis framework
Frederik Bous, Luc Ardaillon, Axel Roebel
This article investigates into recently emerging approaches that use deep neural networks for the estimation of glottal closure instants (GCI). We build upon our previous approach…
eess.AS2019
Analysing Deep Learning-Spectral Envelope Prediction Methods for Singing Synthesis
Frederik Bous, Axel Roebel
We conduct an investigation on various hyper-parameters regarding neural networks used to generate spectral envelopes for singing synthesis. Two perceptive tests, where the first c…