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 …

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 …

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 …

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 …

Anonymisation has the goal of manipulating speech signals in order to degrade the
reliability of automatic approaches to speaker recognition, while preserving other aspects of …

Sharing real-world speech utterances is key to the training and deployment of voice-based
services. However, it also raises privacy risks as speech contains a wealth of personal data …

Speech data conveys sensitive speaker attributes like identity or accent. With a small
amount of found data, such attributes can be inferred and exploited for malicious purposes …

Automatic speech recognition (ASR) is a key technology in many services and applications.
This typically requires user devices to send their speech data to the cloud for ASR decoding …

It is a common feature of modern automated voice-driven applications and services to record
and transmit a user's spoken request. At the same time, several domains and applications …

Internet-connected devices, such as smartphones, smartwatches, and laptops, have become
ubiquitous in modern life, reaching ever deeper into our private spheres. Among the sensors …