collaborators

5 papers

cs.SD2026

Evaluating Parkinson's Disease Detection in Anonymized Speech: A Performance and Acoustic Analysis

Carlos Franzreb, Francisco Teixeira, Ben Luks +2

Automatic detection of Parkinson's disease (PD) from speech is a promising non-invasive diagnostic tool, but it raises significant privacy concerns. Speaker anonymization mitigates…

eess.AS2026

Content Leakage in LibriSpeech and Its Impact on the Privacy Evaluation of Speaker Anonymization

Carlos Franzreb, Arnab Das, Tim Polzehl +1

Speaker anonymization aims to conceal a speaker's identity, without considering the linguistic content. In this study, we reveal a weakness of Librispeech, the dataset that is comm…

eess.AS2026

Improving the Speaker Anonymization Evaluation's Robustness to Target Speakers with Adversarial Learning

Carlos Franzreb, Arnab Das, Tim Polzehl +1

The current privacy evaluation for speaker anonymization often overestimates privacy when a same-gender target selection algorithm (TSA) is used, although this TSA leaks the speake…

cs.SD2025

Generalizable Audio Spoofing Detection using Non-Semantic Representations

Arnab Das, Yassine El Kheir, Carlos Franzreb +3

Rapid advancements in generative modeling have made synthetic audio generation easy, making speech-based services vulnerable to spoofing attacks. Consequently, there is a dire need…

eess.AS2025

Private kNN-VC: Interpretable Anonymization of Converted Speech

Carlos Franzreb, Arnab Das, Tim Polzehl +1

Speaker anonymization seeks to conceal a speaker's identity while preserving the utility of their speech. The achieved privacy is commonly evaluated with a speaker recognition mode…