7 citations · 7 across the 5 of their papers we have counts for
5 papers
Listen to the Features: Voice Anonymization Driven by Content Embedding Matching over Signal Reconstruction
Adrien Schneider, Kacper Zabkowski, Anderson Augusma +3
The paper presents a voice anonymization model focusing on preserving content rather than producing realistic speech. It relies on content embeddings extracted from a frozen pretra…
Multimodal Group Emotion Recognition In-the-Wild Towards a Privacy-Safe Non-Individual Approach
Anderson Augusma
This thesis addresses group emotion recognition (GER) in-the-wild with a focus on privacy preservation. Unlike traditional emotion recognition methods that rely on individual-level…
Variational Encoder--Multi-Decoder (VE-MD) for Privacy-by-functional-design (Group) Emotion Recognition
Anderson Augusma, Dominique Vaufreydaz, Fédérique Letué
Group Emotion Recognition (GER) aims to infer collective affect in social environments such as classrooms, crowds, and public events. Many existing approaches rely on explicit indi…
Exploring VQ-VAE with Prosody Parameters for Speaker Anonymization
Sotheara Leang, Anderson Augusma, Eric Castelli +3
Human speech conveys prosody, linguistic content, and speaker identity. This article investigates a novel speaker anonymization approach using an end-to-end network based on a Vect…
Multimodal Group Emotion Recognition In-the-wild Using Privacy-Compliant Features
Anderson Augusma, Dominique Vaufreydaz, Frédérique Letué
This paper explores privacy-compliant group-level emotion recognition ''in-the-wild'' within the EmotiW Challenge 2023. Group-level emotion recognition can be useful in many fields…