Scenario of Use Scheme: Threat Model Specification for Speaker Privacy Protection in the Medical Domain
Not on the map. Why?
Abstract (arXiv)
Speech recordings are being more frequently used to detect and monitor disease, leading to privacy concerns. Beyond cryptography, protection of speech can be addressed by approaches, such as perturbation, disentanglement, and re-synthesis, that eliminate sensitive information of the speaker, leaving the information necessary for medical analysis purposes. In order for such privacy protective approaches to be developed, clear and systematic specifications of assumptions concerning medical settings and the needs of medical professionals are necessary. In this paper, we propose a Scenario of Use Scheme that incorporates an Attacker Model, which characterizes the adversary against whom the speaker's privacy must be defended, and a Protector Model, which specifies the defense. We discuss the connection of the scheme with previous work on speech privacy. Finally, we present a concrete example of a specified Scenario of Use and a set of experiments about protecting speaker data against gender inference attacks while maintaining utility for Parkinson's detection.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 10 of its 17 references that are in the map. First posted on arXiv 24 Sep 2024.
Builds on
10 of 17 references.
References · 10
- 2014Explaining and Harnessing Adversarial Examplescited by 7,287
- 2017Towards Deep Learning Models Resistant to Adversarial Attackscited by 6,326
- 2020Introducing the VoicePrivacy Initiativecited by 48
- 2024The VoicePrivacy 2024 Challenge Evaluation Plancited by 39
- 2022Anonymizing Speech with Generative Adversarial Networks to Preserve Speaker Privacycited by 20
- 2023Exploring Multimodal Approaches for Alzheimer's Disease Detection Using Patient Speech Transcript and Audio Datacited by 13
- 2024NeuroVoz: a Castillian Spanish corpus of parkinsonian speechcited by 13
- 2022Generating gender-ambiguous voices for privacy-preserving speech recognitioncited by 5
- 2023Alzheimer Disease Classification through ASR-based Transcriptions: Exploring the Impact of Punctuation and Pausescited by 5
- 2023Severity Classification of Parkinson's Disease from Speech using Single Frequency Filtering-based Featurescited by 2
Built on by
Not cited yet.