6 papers
Data Quality as Predictor of Voice Anti-Spoofing Generalization
Bhusan Chettri, Rosa González Hautamäki, Md Sahidullah +1
Voice anti-spoofing aims at classifying a given utterance either as a bonafide human sample, or a spoofing attack (e.g. synthetic or replayed sample). Many anti-spoofing methods ha…
Dataset artefacts in anti-spoofing systems: a case study on the ASVspoof 2017 benchmark
Bhusan Chettri, Emmanouil Benetos, Bob L. T. Sturm
The Automatic Speaker Verification Spoofing and Countermeasures Challenges motivate research in protecting speech biometric systems against a variety of different access attacks. T…
Subband modeling for spoofing detection in automatic speaker verification
Bhusan Chettri, Tomi Kinnunen, Emmanouil Benetos
Spectrograms - time-frequency representations of audio signals - have found widespread use in neural network-based spoofing detection. While deep models are trained on the fullband…
Deep Generative Variational Autoencoding for Replay Spoof Detection in Automatic Speaker Verification
Bhusan Chettri, Tomi Kinnunen, Emmanouil Benetos
Automatic speaker verification (ASV) systems are highly vulnerable to presentation attacks, also called spoofing attacks. Replay is among the simplest attacks to mount - yet diffic…
Ensemble Models for Spoofing Detection in Automatic Speaker Verification
Bhusan Chettri, Daniel Stoller, Veronica Morfi +3
Detecting spoofing attempts of automatic speaker verification (ASV) systems is challenging, especially when using only one modeling approach. For robustness, we use both deep neura…
A Study On Convolutional Neural Network Based End-To-End Replay Anti-Spoofing
Bhusan Chettri, Saumitra Mishra, Bob L. Sturm +1
The second Automatic Speaker Verification Spoofing and Countermeasures challenge (ASVspoof 2017) focused on "replay attack" detection. The best deep-learning systems to compete in…