2 citations · 2 across the 6 of their papers we have counts for
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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…
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…
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…