Search Results for author: Paul-Gauthier Noé

Found 8 papers, 7 papers with code

Explaining a probabilistic prediction on the simplex with Shapley compositions

no code implementations2 Aug 2024 Paul-Gauthier Noé, Miquel Perelló-Nieto, Jean-François Bonastre, Peter Flach

Originating in game theory, Shapley values are widely used for explaining a machine learning model's prediction by quantifying the contribution of each feature's value to the prediction.

Binary Classification Prediction

Revisiting and Improving Scoring Fusion for Spoofing-aware Speaker Verification Using Compositional Data Analysis

1 code implementation16 Jun 2024 Xin Wang, Tomi Kinnunen, Kong Aik Lee, Paul-Gauthier Noé, Junichi Yamagishi

The outcomes of these findings, namely, the score calibration before fusion, improved linear fusion, and better non-linear fusion, were found to be effective on the SASV challenge database.

Speaker Verification

Hiding speaker's sex in speech using zero-evidence speaker representation in an analysis/synthesis pipeline

1 code implementation29 Nov 2022 Paul-Gauthier Noé, Xiaoxiao Miao, Xin Wang, Junichi Yamagishi, Jean-François Bonastre, Driss Matrouf

The use of modern vocoders in an analysis/synthesis pipeline allows us to investigate high-quality voice conversion that can be used for privacy purposes.

Voice Conversion

The VoicePrivacy 2020 Challenge Evaluation Plan

1 code implementation14 May 2022 Natalia Tomashenko, Brij Mohan Lal Srivastava, Xin Wang, Emmanuel Vincent, Andreas Nautsch, Junichi Yamagishi, Nicholas Evans, Jose Patino, Jean-François Bonastre, Paul-Gauthier Noé, Massimiliano Todisco

The VoicePrivacy Challenge aims to promote the development of privacy preservation tools for speech technology by gathering a new community to define the tasks of interest and the evaluation methodology, and benchmarking solutions through a series of challenges.

Benchmarking

Adversarial Disentanglement of Speaker Representation for Attribute-Driven Privacy Preservation

1 code implementation8 Dec 2020 Paul-Gauthier Noé, Mohammad Mohammadamini, Driss Matrouf, Titouan Parcollet, Andreas Nautsch, Jean-François Bonastre

In order to allow the user to choose which information to protect, we introduce in this paper the concept of attribute-driven privacy preservation in speaker voice representation.

Attribute Disentanglement +6

Speech Pseudonymisation Assessment Using Voice Similarity Matrices

2 code implementations30 Aug 2020 Paul-Gauthier Noé, Jean-François Bonastre, Driss Matrouf, Natalia Tomashenko, Andreas Nautsch, Nicholas Evans

The proliferation of speech technologies and rising privacy legislation calls for the development of privacy preservation solutions for speech applications.

De-identification Voice Similarity

Introducing the VoicePrivacy Initiative

3 code implementations4 May 2020 Natalia Tomashenko, Brij Mohan Lal Srivastava, Xin Wang, Emmanuel Vincent, Andreas Nautsch, Junichi Yamagishi, Nicholas Evans, Jose Patino, Jean-François Bonastre, Paul-Gauthier Noé, Massimiliano Todisco

The VoicePrivacy initiative aims to promote the development of privacy preservation tools for speech technology by gathering a new community to define the tasks of interest and the evaluation methodology, and benchmarking solutions through a series of challenges.

Benchmarking

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