3 papers
eess.SP2026
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…
cs.CV2026
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…
cs.CV2026
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…