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- Centre National de la Recherche ScientifiqueFR209 papers
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4 papers · 2 filters
A Comparative Study of Pitch Extraction Algorithms on a Large Variety of Singing Sounds
Onur Babacan, Thomas Drugman, Nicolas d'Alessandro +2
The problem of pitch tracking has been extensively studied in the speech research community. The goal of this paper is to investigate how these techniques should be adapted to sing…
Audio-visual Speech Enhancement Using Conditional Variational Auto-Encoders
Mostafa Sadeghi, Simon Leglaive, Xavier Alameda-PIneda +2
Variational auto-encoders (VAEs) are deep generative latent variable models that can be used for learning the distribution of complex data. VAEs have been successfully used to lear…
Expectation-Maximization for Speech Source Separation Using Convolutive Transfer Function
Xiaofei Li, Laurent Girin, Radu Horaud
This paper addresses the problem of under-determinded speech source separation from multichannel microphone singals, i.e. the convolutive mixtures of multiple sources. The time-dom…
Speech enhancement with variational autoencoders and alpha-stable distributions
Simon Leglaive, Umut Simsekli, Antoine Liutkus +2
This paper focuses on single-channel semi-supervised speech enhancement. We learn a speaker-independent deep generative speech model using the framework of variational autoencoders…