collaborators

8 papers

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

A Parameter-Efficient Multi-Scale Convolutional Adapter for Synthetic Speech Detection

Yassine El Kheir, Fabian Ritter-Guttierez, Arnab Das +2

Recent synthetic speech detection models typically adapt a pre-trained SSL model via finetuning, which is computationally demanding. Parameter-Efficient Fine-Tuning (PEFT) offers a…

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…

cs.SD2025

Two Views, One Truth: Spectral and Self-Supervised Features Fusion for Robust Speech Deepfake Detection

Yassine El Kheir, Arnab Das, Enes Erdem Erdogan +3

Recent advances in synthetic speech have made audio deepfakes increasingly realistic, posing significant security risks. Existing detection methods that rely on a single modality,…

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…