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SpecWav-Attack: Leveraging Spectrogram Resizing and Wav2Vec 2.0 for Attacking Anonymized Speech

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arxiv 2505.09616 v1 pith:WX3OBI7T submitted 2025-01-10 cs.SD cs.AIeess.AS

SpecWav-Attack: Leveraging Spectrogram Resizing and Wav2Vec 2.0 for Attacking Anonymized Speech

Yuqi Li , Yuanzhong Zheng , Zhongtian Guo , Yaoxuan Wang , Jianjun Yin , Haojun Fei This is my paper
classification cs.SD cs.AIeess.AS
keywords anonymizedspecwav-attackspeechresizingspectrogramadversarialattackerattacking
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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This paper presents SpecWav-Attack, an adversarial model for detecting speakers in anonymized speech. It leverages Wav2Vec2 for feature extraction and incorporates spectrogram resizing and incremental training for improved performance. Evaluated on librispeech-dev and librispeech-test, SpecWav-Attack outperforms conventional attacks, revealing vulnerabilities in anonymized speech systems and emphasizing the need for stronger defenses, benchmarked against the ICASSP 2025 Attacker Challenge.

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