12 citations · 12 across the 1 of their papers we have counts for
8 papers
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…
Reliable Local Explanations for Machine Listening
Saumitra Mishra, Emmanouil Benetos, Bob L. Sturm +1
One way to analyse the behaviour of machine learning models is through local explanations that highlight input features that maximally influence model predictions. Sensitivity anal…
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…
The "Horse'' Inside: Seeking Causes Behind the Behaviours of Music Content Analysis Systems
Bob L. Sturm
Building systems that possess the sensitivity and intelligence to identify and describe high-level attributes in music audio signals continues to be an elusive goal, but one that s…
Music transcription modelling and composition using deep learning
Bob L. Sturm, João Felipe Santos, Oded Ben-Tal +1
We apply deep learning methods, specifically long short-term memory (LSTM) networks, to music transcription modelling and composition. We build and train LSTM networks using approx…