26 citations · 44 across the 9 of their papers we have counts for
4 papers · 1 filter
Speaker anonymisation using the McAdams coefficient
Jose Patino, Natalia Tomashenko, Massimiliano Todisco +2
Anonymisation has the goal of manipulating speech signals in order to degrade the reliability of automatic approaches to speaker recognition, while preserving other aspects of spee…
Speech Pseudonymisation Assessment Using Voice Similarity Matrices
Paul-Gauthier Noé, Jean-François Bonastre, Driss Matrouf +3
The proliferation of speech technologies and rising privacy legislation calls for the development of privacy preservation solutions for speech applications. These are essential sin…
Design Choices for X-vector Based Speaker Anonymization
Brij Mohan Lal Srivastava, Natalia Tomashenko, Xin Wang +5
The recently proposed x-vector based anonymization scheme converts any input voice into that of a random pseudo-speaker. In this paper, we present a flexible pseudo-speaker selecti…
Exploring Gaussian mixture model framework for speaker adaptation of deep neural network acoustic models
Natalia Tomashenko, Yuri Khokhlov, Yannick Esteve
In this paper we investigate the GMM-derived (GMMD) features for adaptation of deep neural network (DNN) acoustic models. The adaptation of the DNN trained on GMMD features is done…