arxiveess.SPcs.AI2026-07-07
Listen to the Features: Voice Anonymization Driven by Content Embedding Matching over Signal Reconstruction
Adrien Schneider, Kacper Zabkowski, Anderson Augusma, Frédérique Letué, Maria Camila Pinzon, Dominique Vaufreydaz
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 pretrained wav2vec2 encoder. These embeddings are decoded into an anonymized signal using vector quantizat…