Open access paper published in cooperation of Hochschule Darmstadt and TU Darmstadt

Together with international experts, CRISP scientists from Hochschule Darmstadt and TU Darmstadt investigated privacy protection schemes for speaker recognition applications. The paper entitled „Preserving privacy in speech and speech characterization“, was worked out as part an extensive and interdisciplinary collaboration am various researchers, is now published in the renowned journal Computer Speech and Language (link auf: https://www.journals.elsevier.com/computer-speech-and-language)

The team of authors includes: Andreas Nautsch, Abelino Jiménez, Amos Treiber, Jascha Kolberg, Catherine Jasserand, Els Kindt, Héctor Delgado, Massimiliano Todisco, Mohamed Amine Hmani, Aymen Mtibaa, Mohammed Ahmed Abdelraheem, Alberto Abad, Francisco Teixeira, Driss Matrouf, Marta Gomez-Barrero, Dijana Petrovska-Delacrétaz, Gérard Chollet, Nicholas Evans, Thomas Schneider, Jean-François Bonastre, Bhiksha Raj, Isabel Trancoso, and Christoph Busch. This team is an international cooperation of Hochschule Darmstadt with TU Darmstadt, CMU Pittsburgh (US), University of Groningen (NL), KU Leuven (BE),  EURECOM (FR), Télécom SudParis (FR), Intelligent Voice Ltd. (FR), University of Lisbon (PT) and Université d’Avignon (FR).

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.

Open access paper published in cooperation of Hochschule Darmstadt and TU Darmstadt