A survey on differential privacy for unstructured data content

Y Zhao, J Chen - ACM Computing Surveys (CSUR), 2022 - dl.acm.org
Huge amounts of unstructured data including image, video, audio, and text are ubiquitously
generated and shared, and it is a challenge to protect sensitive personal information in …

Speaker identification features extraction methods: A systematic review

SS Tirumala, SR Shahamiri, AS Garhwal… - Expert Systems with …, 2017 - Elsevier
Speaker Identification (SI) is the process of identifying the speaker from a given utterance by
comparing the voice biometrics of the utterance with those utterance models stored …

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

S Ribaric, A Ariyaeeinia, N Pavesic - Signal Processing: Image …, 2016 - Elsevier
Privacy 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 …

Speaker anonymization using x-vector and neural waveform models

F Fang, X Wang, J Yamagishi, I Echizen… - arxiv preprint arxiv …, 2019 - arxiv.org
The social media revolution has produced a plethora of web services to which users can
easily upload and share multimedia documents. Despite the popularity and convenience of …

Privacy–enhancing face biometrics: A comprehensive survey

B Meden, P Rot, P Terhörst, N Damer… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Biometric recognition technology has made significant advances over the last decade and is
now used across a number of services and applications. However, this widespread …

[HTML][HTML] X-vector anonymization using autoencoders and adversarial training for preserving speech privacy

JM Perero-Codosero, FM Espinoza-Cuadros… - Computer speech & …, 2022 - Elsevier
The rapid increase in web services and mobile apps, which collect personal data from users,
has also increased the risk that their privacy may be severely compromised. In particular, the …

Design choices for x-vector based speaker anonymization

BML Srivastava, N Tomashenko, X Wang… - arxiv preprint arxiv …, 2020 - arxiv.org
The recently proposed x-vector based anonymization scheme converts any input voice into
that of a random pseudo-speaker. In this paper, we present a flexible pseudo-speaker …

Voice-indistinguishability: Protecting voiceprint in privacy-preserving speech data release

Y Han, S Li, Y Cao, Q Ma… - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
With the development of smart devices, such as the Amazon Echo and Apple's HomePod,
speech data have become a new dimension of big data. However, privacy and security …

Security, privacy, and robustness for trustworthy AI systems: A review

MM Saeed, M Alsharidah - Computers and Electrical Engineering, 2024 - Elsevier
This review article provides a comprehensive exploration of the key pillars of trustworthy AI:
security privacy and robustness. The article delved into security measures both traditional …

Privacy and utility of x-vector based speaker anonymization

BML Srivastava, M Maouche… - … on Audio, Speech …, 2022 - ieeexplore.ieee.org
We study the scenario where individuals (speakers) contribute to the publication of an
anonymized speech corpus. Data users leverage this public corpus for downstream tasks …