106 citations · 269 across the 10 of their papers we have counts for
12 papers
New Challenges for Content Privacy in Speech and Audio
Jennifer Williams, Karla Pizzi, Shuvayanti Das +1
Privacy in speech and audio has many facets. A particularly under-developed area of privacy in this domain involves consideration for information related to content and context. Sp…
Hiding speaker's sex in speech using zero-evidence speaker representation in an analysis/synthesis pipeline
Paul-Gauthier Noé, Xiaoxiao Miao, Xin Wang +3
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. Here, we propose to trans…
The VoicePrivacy 2020 Challenge Evaluation Plan
Natalia Tomashenko, Brij Mohan Lal Srivastava, Xin Wang +8
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…
Revisiting Speech Content Privacy
Jennifer Williams, Junichi Yamagishi, Paul-Gauthier Noe +2
In this paper, we discuss an important aspect of speech privacy: protecting spoken content. New capabilities from the field of machine learning provide a unique and timely opportun…
A bridge between features and evidence for binary attribute-driven perfect privacy
Paul-Gauthier Noé, Andreas Nautsch, Driss Matrouf +2
Attribute-driven privacy aims to conceal a single user's attribute, contrary to anonymisation that tries to hide the full identity of the user in some data. When the attribute to p…
The VoicePrivacy 2020 Challenge: Results and findings
Natalia Tomashenko, Xin Wang, Emmanuel Vincent +11
This paper presents the results and analyses stemming from the first VoicePrivacy 2020 Challenge which focuses on developing anonymization solutions for speech technology. We provi…
Benchmarking and challenges in security and privacy for voice biometrics
Jean-Francois Bonastre, Hector Delgado, Nicholas Evans +13
For many decades, research in speech technologies has focused upon improving reliability. With this now meeting user expectations for a range of diverse applications, speech techno…
Adversarial Disentanglement of Speaker Representation for Attribute-Driven Privacy Preservation
Paul-Gauthier Noé, Mohammad Mohammadamini, Driss Matrouf +3
In speech technologies, speaker's voice representation is used in many applications such as speech recognition, voice conversion, speech synthesis and, obviously, user authenticati…
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…
The Privacy ZEBRA: Zero Evidence Biometric Recognition Assessment
Andreas Nautsch, Jose Patino, Natalia Tomashenko +5
Mounting privacy legislation calls for the preservation of privacy in speech technology, though solutions are gravely lacking. While evaluation campaigns are long-proven tools to d…
Introducing the VoicePrivacy Initiative
Natalia Tomashenko, Brij Mohan Lal Srivastava, Xin Wang +8
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…
CGCNN: Complex Gabor Convolutional Neural Network on raw speech
Paul-Gauthier Noé, Titouan Parcollet, Mohamed Morchid
Convolutional Neural Networks (CNN) have been used in Automatic Speech Recognition (ASR) to learn representations directly from the raw signal instead of hand-crafted acoustic feat…