Intelligibility Assessment of the De-Identified Speech Obtained Using Phoneme Recognition and Speech Synthesis Systems

Justin, Tadej; Dobrišek, Simon

doi:10.1007/978-3-319-10816-2_64

Cited by 2 publications

(1 citation statement)

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“…The assessment of the de-identification of behavioural biometric identifiers is mainly devoted to privacy protection and to the intelligibility of de-identified speech [203].…”

Section: Discussionmentioning

confidence: 99%

De-identification for privacy protection in multimedia content: A survey

Ribarić

Ariyaeeinia

Pavešić

2016

Signal Processing: Image Communication

145

107

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a b s t r a c tPrivacy is one of the most important social and political issues in our information society, characterized by a growing range of enabling and supporting technologies and services. Amongst these are communications, multimedia, biometrics, big data, cloud computing, data mining, internet, social networks, and audio-video surveillance. Each of these can potentially provide the means for privacy intrusion. Deidentification is one of the main approaches to privacy protection in multimedia contents (text, still images, audio and video sequences and their combinations). It is a process for concealing or removing personal identifiers, or replacing them by surrogate personal identifiers in personal information in order to prevent the disclosure and use of data for purposes unrelated to the purpose for which the information was originally obtained. Based on the proposed taxonomy inspired by the Safe Harbour approach, the personal identifiers, i.e., the personal identifiable information, are classified as non-biometric, physiological and behavioural biometric, and soft biometric identifiers. In order to protect the privacy of an individual, all of the above identifiers will have to be de-identified in multimedia content. This paper presents a review of the concepts of privacy and the linkage among privacy, privacy protection, and the methods and technologies designed specifically for privacy protection in multimedia contents. The study provides an overview of de-identification approaches for non-biometric identifiers (text, hairstyle, dressing style, license plates), as well as for the physiological (face, fingerprint, iris, ear), behavioural (voice, gait, gesture) and soft-biometric (body silhouette, gender, age, race, tattoo) identifiers in multimedia documents.

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“…The assessment of the de-identification of behavioural biometric identifiers is mainly devoted to privacy protection and to the intelligibility of de-identified speech [203].…”

Section: Discussionmentioning

confidence: 99%