Pinhole Effect on Linkability and Dispersion in Speaker Anonymization

TL;DR

This paper explores how different speaker pseudo-mapping strategies affect anonymization effectiveness, introducing the 'pinhole effect' as a conceptual framework validated through empirical analysis.

Contribution

It introduces the 'pinhole effect' to explain the impact of mapping strategies on speaker anonymization, highlighting the benefits of using distinct pseudo speakers.

Findings

Distinct pseudo speakers increase dispersion and reduce linkability.

Common pseudo speakers lead to lower dispersion and higher linkability.

The pinhole effect explains the relationship between mapping strategies and privacy.

Abstract

Speaker anonymization aims to conceal speaker-specific attributes in speech signals, making the anonymized speech unlinkable to the original speaker identity. Recent approaches achieve this by disentangling speech into content and speaker components, replacing the latter with pseudo speakers. The anonymized speech can be mapped either to a common pseudo speaker shared across utterances or to distinct pseudo speakers unique to each utterance. This paper investigates the impact of these mapping strategies on three key dimensions: speaker linkability, dispersion in the anonymized speaker space, and de-identification from the original identity. Our findings show that using distinct pseudo speakers increases speaker dispersion and reduces linkability compared to common pseudo-speaker mapping, thereby enhancing privacy preservation. These observations are interpreted through the proposed pinhole effect, a conceptual framework introduced to explain the relationship between mapping strategies and anonymization performance. The hypothesis is validated through empirical evaluation.