ASCLCRApr 19, 2025

The First VoicePrivacy Attacker Challenge

arXiv:2504.14183v112 citationsh-index: 24ICASSP
Originality Synthesis-oriented
AI Analysis

This work addresses the need for robust evaluation of privacy attacks in voice anonymization, though it is incremental as it builds on prior challenges.

The paper tackled the problem of evaluating attacker systems against voice anonymization methods by organizing the First VoicePrivacy Attacker Challenge, where the best systems reduced the equal error rate by 25-44% relative to a baseline.

The First VoicePrivacy Attacker Challenge is an ICASSP 2025 SP Grand Challenge which focuses on evaluating attacker systems against a set of voice anonymization systems submitted to the VoicePrivacy 2024 Challenge. Training, development, and evaluation datasets were provided along with a baseline attacker. Participants developed their attacker systems in the form of automatic speaker verification systems and submitted their scores on the development and evaluation data. The best attacker systems reduced the equal error rate (EER) by 25-44% relative w.r.t. the baseline.

Foundations

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