1 citations · 2 across the 6 of their papers we have counts for
5 papers · 1 filter
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,…
Voice Reenactment with F0 and timing constraints and adversarial learning of conversions
Frederik Bous, Laurent Benaroya, Nicolas Obin +1
This paper introduces voice reenactement as the task of voice conversion (VC) in which the expressivity of the source speaker is preserved during conversion while the identity of a…
Beyond Voice Identity Conversion: Manipulating Voice Attributes by Adversarial Learning of Structured Disentangled Representations
Laurent Benaroya, Nicolas Obin, Axel Roebel
Voice conversion (VC) consists of digitally altering the voice of an individual to manipulate part of its content, primarily its identity, while maintaining the rest unchanged. Res…
Speaker Attentive Speech Emotion Recognition
Clément Le Moine, Nicolas Obin, Axel Roebel
Speech Emotion Recognition (SER) task has known significant improvements over the last years with the advent of Deep Neural Networks (DNNs). However, even the most successful metho…
Towards end-to-end F0 voice conversion based on Dual-GAN with convolutional wavelet kernels
Clément Le Moine Veillon, Nicolas Obin, Axel Roebel
This paper presents a end-to-end framework for the F0 transformation in the context of expressive voice conversion. A single neural network is proposed, in which a first module is…