On the invertibility of a voice privacy system using embedding alignement

• URL: http://arxiv.org/abs/2110.05431v1
• Date: Fri, 8 Oct 2021 14:43:47 GMT
• Title: On the invertibility of a voice privacy system using embedding alignement
• Authors: Pierre Champion (MULTISPEECH, LIUM), Thomas Thebaud (LIUM), Ga\"el Le Lan, Anthony Larcher (LIUM), Denis Jouvet (MULTISPEECH)
• Abstract summary: This paper explores various attack scenarios on a voice anonymization system using embeddings alignment techniques. We compute the optimal rotation and compare the results of this approximation to the official Voice Privacy Challenge results.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper explores various attack scenarios on a voice anonymization system using embeddings alignment techniques. We use Wasserstein-Procrustes (an algorithm initially designed for unsupervised translation) or Procrustes analysis to match two sets of x-vectors, before and after voice anonymization, to mimic this transformation as a rotation function. We compute the optimal rotation and compare the results of this approximation to the official Voice Privacy Challenge results. We show that a complex system like the baseline of the Voice Privacy Challenge can be approximated by a rotation, estimated using a limited set of x-vectors. This paper studies the space of solutions for voice anonymization within the specific scope of rotations. Rotations being reversible, the proposed method can recover up to 62% of the speaker identities from anonymized embeddings.

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