5 citations · 9 across the 7 of their papers we have counts for
8 papers
Self-supervised learning with diffusion-based multichannel speech enhancement for speaker verification under noisy conditions
Sandipana Dowerah, Ajinkya Kulkarni, Romain Serizel +1
The paper introduces Diff-Filter, a multichannel speech enhancement approach based on the diffusion probabilistic model, for improving speaker verification performance under noisy…
Evaluation of Speaker Anonymization on Emotional Speech
Hubert Nourtel, Pierre Champion, Denis Jouvet +2
Speech data carries a range of personal information, such as the speaker's identity and emotional state. These attributes can be used for malicious purposes. With the development o…
How to Leverage DNN-based speech enhancement for multi-channel speaker verification?
Sandipana Dowerah, Romain Serizel, Denis Jouvet +2
Speaker verification (SV) suffers from unsatisfactory performance in far-field scenarios due to environmental noise andthe adverse impact of room reverberation. This work presents…
Are disentangled representations all you need to build speaker anonymization systems?
Pierre Champion, Denis Jouvet, Anthony Larcher
Speech signals contain a lot of sensitive information, such as the speaker's identity, which raises privacy concerns when speech data get collected. Speaker anonymization aims to t…
Privacy-Preserving Speech Representation Learning using Vector Quantization
Pierre Champion, Denis Jouvet, Anthony Larcher
With the popularity of virtual assistants (e.g., Siri, Alexa), the use of speech recognition is now becoming more and more widespread.However, speech signals contain a lot of sensi…
On the invertibility of a voice privacy system using embedding alignement
Pierre Champion, Thomas Thebaud, Gaël Le Lan +2
This paper explores various attack scenarios on a voice anonymization system using embeddings alignment techniques. We use Wasserstein-Procrustes (an algorithm initially designed f…
Evaluating X-vector-based Speaker Anonymization under White-box Assessment
Pierre Champion, Denis Jouvet, Anthony Larcher
In the scenario of the Voice Privacy challenge, anonymization is achieved by converting all utterances from a source speaker to match the same target identity; this identity being…
A Study of F0 Modification for X-Vector Based Speech Pseudonymization Across Gender
Pierre Champion, Denis Jouvet, Anthony Larcher
Speech pseudonymization aims at altering a speech signal to map the identifiable personal characteristics of a given speaker to another identity. In other words, it aims to hide th…