Voice anonymization (VA) is used to conceal the voice identities in speech data. Performance is usually estimated using automatic speaker verification (ASV) as a proxy to judge the capability of an attacker to re-identify speakers after anonymization. The defender anonymizes test utterances; the attacker compares them...
M. Panariello, Yi-Bo Bai, Massimiliano Todisco et al.· 0 citations
Accent conversion is the task of modifying a speech recording so that it sounds closer to a target accent while preserving linguistic content and other speaker-related characteristics. Most accent conversion systems use trained, generative models. Although they can induce target-accented speech, the strength of accent...
Yang-Yang Qu, M. Panariello, Massimiliano Todisco et al.· 0 citations
We study speaker-disjoint accent identification for L2 English, where the goal is to predict a speaker's first-language (L1) background from English pronunciation. Most existing systems classify accents using a single utterance-level representation, but such global representations can obscure pronunciation cues that de...
Yang-Yang Qu, Massimiliano Todisco, Nicholas W. D. Evans· 1 citation
The Positive-Incentive Noise Predictor (PnP) is proposed, the first framework that explicitly introduces positive-incentive noise ({\pi}-noise) into the purification task and effectively defends against adversarial attacks while preserving performance on natural speech.
Yibo Bai, Sizhou Chen, M. Panariello et al.· 0 citations
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