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Found 5 papers, 1 papers with code
How to Construct Perfect and Worse-than-Coin-Flip Spoofing Countermeasures: A Word of Warning on Shortcut Learning
Shortcut learning, or `Clever Hans effect` refers to situations where a learning agent (e. g., deep neural networks) learns spurious correlations present in data, resulting in biased models.
Improving speaker de-identification with functional data analysis of f0 trajectories
Due to a constantly increasing amount of speech data that is stored in different types of databases, voice privacy has become a major concern.
Data Quality as Predictor of Voice Anti-Spoofing Generalization
Voice anti-spoofing aims at classifying a given utterance either as a bonafide human sample, or a spoofing attack (e. g. synthetic or replayed sample).
Voice Mimicry Attacks Assisted by Automatic Speaker Verification
Our goal is to gain insights how well similarity rankings transfer from the attacker's ASV system to the attacked ASV system, whether the attackers are able to improve their attacks by mimicking, and how the properties of the voices of attackers change due to mimicking.
Can We Use Speaker Recognition Technology to Attack Itself? Enhancing Mimicry Attacks Using Automatic Target Speaker Selection
We consider technology-assisted mimicry attacks in the context of automatic speaker verification (ASV).
