131 citations · 433 across the 22 of their papers we have counts for
25 papers
A False Sense of Privacy: Towards a Reliable Evaluation Methodology for the Anonymization of Biometric Data
Simon Hanisch, Julian Todt, Jose Patino +2
Biometric data contains distinctive human traits such as facial features or gait patterns. The use of biometric data permits an individuation so exact that the data is utilized eff…
ASVspoof 2021: Towards Spoofed and Deepfake Speech Detection in the Wild
Xuechen Liu, Xin Wang, Md Sahidullah +8
Benchmarking initiatives support the meaningful comparison of competing solutions to prominent problems in speech and language processing. Successive benchmarking evaluations typic…
The VoicePrivacy 2020 Challenge Evaluation Plan
Natalia Tomashenko, Brij Mohan Lal Srivastava, Xin Wang +8
The VoicePrivacy Challenge aims to promote the development of privacy preservation tools for speech technology by gathering a new community to define the tasks of interest and the…
Exploring auditory acoustic features for the diagnosis of the Covid-19
Madhu R. Kamble, Jose Patino, Maria A. Zuluaga +1
The current outbreak of a coronavirus, has quickly escalated to become a serious global problem that has now been declared a Public Health Emergency of International Concern by the…
RawBoost: A Raw Data Boosting and Augmentation Method applied to Automatic Speaker Verification Anti-Spoofing
Hemlata Tak, Madhu Kamble, Jose Patino +2
This paper introduces RawBoost, a data boosting and augmentation method for the design of more reliable spoofing detection solutions which operate directly upon raw waveform inputs…
Explaining deep learning models for spoofing and deepfake detection with SHapley Additive exPlanations
Wanying Ge, Jose Patino, Massimiliano Todisco +1
Substantial progress in spoofing and deepfake detection has been made in recent years. Nonetheless, the community has yet to make notable inroads in providing an explanation for ho…
The VoicePrivacy 2020 Challenge: Results and findings
Natalia Tomashenko, Xin Wang, Emmanuel Vincent +11
This paper presents the results and analyses stemming from the first VoicePrivacy 2020 Challenge which focuses on developing anonymization solutions for speech technology. We provi…
ASVspoof 2021: accelerating progress in spoofed and deepfake speech detection
Junichi Yamagishi, Xin Wang, Massimiliano Todisco +8
ASVspoof 2021 is the forth edition in the series of bi-annual challenges which aim to promote the study of spoofing and the design of countermeasures to protect automatic speaker v…
ASVspoof 2021: Automatic Speaker Verification Spoofing and Countermeasures Challenge Evaluation Plan
Héctor Delgado, Nicholas Evans, Tomi Kinnunen +8
The automatic speaker verification spoofing and countermeasures (ASVspoof) challenge series is a community-led initiative which aims to promote the consideration of spoofing and th…
Benchmarking and challenges in security and privacy for voice biometrics
Jean-Francois Bonastre, Hector Delgado, Nicholas Evans +13
For many decades, research in speech technologies has focused upon improving reliability. With this now meeting user expectations for a range of diverse applications, speech techno…
End-to-End Spectro-Temporal Graph Attention Networks for Speaker Verification Anti-Spoofing and Speech Deepfake Detection
Hemlata Tak, Jee-weon Jung, Jose Patino +3
Artefacts that serve to distinguish bona fide speech from spoofed or deepfake speech are known to reside in specific subbands and temporal segments. Various approaches can be used…
Raw Differentiable Architecture Search for Speech Deepfake and Spoofing Detection
Wanying Ge, Jose Patino, Massimiliano Todisco +1
End-to-end approaches to anti-spoofing, especially those which operate directly upon the raw signal, are starting to be competitive with their more traditional counterparts. Until…
PANACEA cough sound-based diagnosis of COVID-19 for the DiCOVA 2021 Challenge
Madhu R. Kamble, Jose A. Gonzalez-Lopez, Teresa Grau +11
The COVID-19 pandemic has led to the saturation of public health services worldwide. In this scenario, the early diagnosis of SARS-Cov-2 infections can help to stop or slow the spr…
Graph Attention Networks for Anti-Spoofing
Hemlata Tak, Jee-weon Jung, Jose Patino +2
The cues needed to detect spoofing attacks against automatic speaker verification are often located in specific spectral sub-bands or temporal segments. Previous works show the pot…
Partially-Connected Differentiable Architecture Search for Deepfake and Spoofing Detection
Wanying Ge, Michele Panariello, Jose Patino +2
This paper reports the first successful application of a differentiable architecture search (DARTS) approach to the deepfake and spoofing detection problems. An example of neural a…
An Initial Investigation for Detecting Partially Spoofed Audio
Lin Zhang, Xin Wang, Erica Cooper +3
All existing databases of spoofed speech contain attack data that is spoofed in its entirety. In practice, it is entirely plausible that successful attacks can be mounted with utte…
Biometrics in the Era of COVID-19: Challenges and Opportunities
Marta Gomez-Barrero, Pawel Drozdowski, Christian Rathgeb +7
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 rate…
Speaker anonymisation using the McAdams coefficient
Jose Patino, Natalia Tomashenko, Massimiliano Todisco +2
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 spee…
End-to-end anti-spoofing with RawNet2
Hemlata Tak, Jose Patino, Massimiliano Todisco +3
Spoofing countermeasures aim to protect automatic speaker verification systems from attempts to manipulate their reliability with the use of spoofed speech signals. While results f…
Texture-based Presentation Attack Detection for Automatic Speaker Verification
Lazaro J. Gonzalez-Soler, Jose Patino, Marta Gomez-Barrero +3
Biometric systems are nowadays employed across a broad range of applications. They provide high security and efficiency and, in many cases, are user friendly. Despite these and oth…
Spoofing Attack Detection using the Non-linear Fusion of Sub-band Classifiers
Hemlata Tak, Jose Patino, Andreas Nautsch +2
The threat of spoofing can pose a risk to the reliability of automatic speaker verification. Results from the bi-annual ASVspoof evaluations show that effective countermeasures dem…
The Privacy ZEBRA: Zero Evidence Biometric Recognition Assessment
Andreas Nautsch, Jose Patino, Natalia Tomashenko +5
Mounting privacy legislation calls for the preservation of privacy in speech technology, though solutions are gravely lacking. While evaluation campaigns are long-proven tools to d…
Introducing the VoicePrivacy Initiative
Natalia Tomashenko, Brij Mohan Lal Srivastava, Xin Wang +8
The VoicePrivacy initiative aims to promote the development of privacy preservation tools for speech technology by gathering a new community to define the tasks of interest and the…
An explainability study of the constant Q cepstral coefficient spoofing countermeasure for automatic speaker verification
Hemlata Tak, Jose Patino, Andreas Nautsch +2
Anti-spoofing for automatic speaker verification is now a well established area of research, with three competitive challenges having been held in the last 6 years. A great deal of…