Preserving privacy in speaker and speech characterisation. (November 2019)

• Record Type: Journal Article
• Authors: Nautsch, Andreas; Jiménez, Abelino; Treiber, Amos; Kolberg, Jascha; Jasserand, Catherine; Kindt, Els; Delgado, Héctor; Todisco, Massimiliano; Hmani, Mohamed Amine; Mtibaa, Aymen; Abdelraheem, Mohammed Ahmed; Abad, Alberto; Teixeira, Francisco; Matrouf, Driss; Gomez-Barrero, Marta; Petrovska-Delacrétaz, Dijana; Chollet, Gérard; Evans, Nicholas; Schneider, Thomas; Bonastre, Jean-François; Raj, Bhiksha; Trancoso, Isabel; Busch, Christoph
• Is Part Of: Computer speech & language. Volume 58(2019)
• Page Start: 441
• Page End: 480
• Publication Date: 2019-11
• Subjects: Data privacy -- Voice biometrics -- Standardisation -- Cryptography -- Legislation; Speech processing systems -- Periodicals; Automatic speech recognition -- Periodicals; Computers -- Periodicals; Linguistics -- Periodicals; Speech-Language Pathology -- Periodicals; Traitement automatique de la parole -- Périodiques; Reconnaissance automatique de la parole -- Périodiques; Automatic speech recognition; Speech processing systems; Electronic journals; Periodicals; 006.454
• DOI: 10.1016/j.csl.2019.06.001
• Languages: English
• ISSNs: 0885-2308

Abstract

Highlights: Speech data in legislation. Standards on biometric information protection. Speaker recognition, for the non-expert. Technology survey: data privacy for speech and speaker recognition. Proposed harmonised evaluation measures. Abstract: Speech recordings are a rich source of personal, sensitive data that can be used to support a plethora of diverse applications, from health profiling to biometric recognition. It is therefore essential that speech recordings are adequately protected so that they cannot be misused. Such protection, in the form of privacy-preserving technologies, is required to ensure that: (i) the biometric profiles of a given individual (e.g., across different biometric service operators) are unlinkable ; (ii) leaked, encrypted biometric information is irreversible, and that (iii) biometric references are renewable . Whereas many privacy-preserving technologies have been developed for other biometric characteristics, very few solutions have been proposed to protect privacy in the case of speech signals. Despite privacy preservation this is now being mandated by recent European and international data protection regulations. With the aim of fostering progress and collaboration between researchers in the speech, biometrics and applied cryptography communities, this survey article provides an introduction to the field, starting with a legal perspective on privacy preservation in the case of speech data . It then establishes the requirements for effective privacy preservation, reviews generic cryptography-based solutions, followed by specific techniques that are applicable to speaker characterisation (biometric applications) and speech characterisation (non-biometric applications). Glancing at non-biometrics, methods are presented to avoid function creep, preventing the exploitation of biometric information, e.g., to single out an identity in speech-assisted health care via speaker characterisation. In promoting harmonised research, the article also outlines common, empirical evaluation metrics for the assessment of privacy-preserving technologies for speech data.