Since early 2020, the COVID-19 pandemic has had a considerable impact on many aspects
of daily life. A range of different measures have been implemented worldwide to reduce the …

The prevalent commercial deployment of mobile biometrics as a robust authentication
method on mobile devices has fueled increasingly scientific attention. Motivated by this, in …

Automated speaker recognition uses data processing to identify speakers by their voice.
Today, automated speaker recognition is deployed on billions of smart devices and in …

In this paper, we build a speech privacy attack that exploits speech reverberations from a
smartphone's inbuilt loudspeaker captured via a zero-permission motion sensor …

In this paper, we introduce Spear, an open source and extensible toolbox for state-of-the-art
speaker recognition. This toolbox is built on top of Bob, a free signal processing and …

In this paper, we build a speech privacy attack that exploits speech reverberations
generated from a smartphone's inbuilt loudspeaker 1 captured via a zero-permission motion …

Automatic Speaker Recognition systems show interesting properties, such as speed of
processing or repeatability of results, in contrast to speaker recognition by humans. But they …

Deep neural networks are inherently opaque and challenging to interpret. Unlike hand-
crafted feature-based models, we struggle to comprehend the concepts learned and how …

Automatic face recognition in unconstrained environments is a challenging task. To test
current trends in face recognition algorithms, we organized an evaluation on face …

We propose an audio-visual person identification approach based on a joint deep
Boltzmann machine (jDBM) model. The proposed jDBM model is trained in three steps: 1) …