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Found 12 papers, 1 papers with code
VaSAB: The variable size adaptive information bottleneck for disentanglement on speech and singing voice
The information bottleneck auto-encoder is a tool for disentanglement commonly used for voice transformation.
AI (r)evolution -- where are we heading? Thoughts about the future of music and sound technologies in the era of deep learning
The students represent the future generation of AI and music researchers.
Analysis and transformations of voice level in singing voice
We introduce the recording factor that relates the voice level to the recorded signal power as a proportionality constant.
Audio Defect Detection in Music with Deep Networks
The ability of our models to capture variance is explored in a detector for artefacts from decompression of corrupted MP3 compressed audio.
Towards Universal Neural Vocoding with a Multi-band Excited WaveNet
This paper introduces the Multi-Band Excited WaveNet a neural vocoder for speaking and singing voices.
Beyond Voice Identity Conversion: Manipulating Voice Attributes by Adversarial Learning of Structured Disentangled Representations
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.
Speaker Attentive Speech Emotion Recognition
Speech Emotion Recognition (SER) task has known significant improvements over the last years with the advent of Deep Neural Networks (DNNs).
Towards end-to-end F0 voice conversion based on Dual-GAN with convolutional wavelet kernels
A single neural network is proposed, in which a first module is used to learn F0 representation over different temporal scales and a second adversarial module is used to learn the transformation from one emotion to another.
La voix act\'ee : pratiques, enjeux, applications (Acted voice : practices, challenges, applications)
La voix act{\'e}e repr{\'e}sente un d{\'e}fi majeur pour les futures interfaces vocales avec un potentiel d{'}application extr{\^e}mement important pour la transformation num{\'e}rique des secteurs de la culture et de la communication, comme la production ou la post-production de voix pour les s{\'e}ries ou le cin{\'e}ma.
GCI detection from raw speech using a fully-convolutional network
Following this trend, we propose here a simple approach that performs a regression from the speech waveform to a target signal from which the GCI are easily obtained by peak-picking.
CycleGAN Voice Conversion of Spectral Envelopes using Adversarial Weights
This paper tackles GAN optimization and stability issues in the context of voice conversion.
An evaluation framework for event detection using a morphological model of acoustic scenes
This paper introduces a model of environmental acoustic scenes which adopts a morphological approach by ab-stracting temporal structures of acoustic scenes.
