28 citations · 271 across the 94 of their papers we have counts for
9 papers · 1 filter
Modeling plate and spring reverberation using a DSP-informed deep neural network
Marco A. Martínez Ramírez, Emmanouil Benetos, Joshua D. Reiss
Plate and spring reverberators are electromechanical systems first used and researched as means to substitute real room reverberation. Nowadays they are often used in music product…
Adversarial Attacks in Sound Event Classification
Vinod Subramanian, Emmanouil Benetos, Ning Xu +2
Adversarial attacks refer to a set of methods that perturb the input to a classification model in order to fool the classifier. In this paper we apply different gradient based adve…
Polyphonic Sound Event and Sound Activity Detection: A Multi-task approach
Arjun Pankajakshan, Helen L. Bear, Emmanouil Benetos
Polyphonic Sound Event Detection (SED) in real-world recordings is a challenging task because of the dynamic polyphony level, intensity, and duration of sound events. Current polyp…
A general-purpose deep learning approach to model time-varying audio effects
Marco A. Martínez Ramírez, Emmanouil Benetos, Joshua D. Reiss
Audio processors whose parameters are modified periodically over time are often referred as time-varying or modulation based audio effects. Most existing methods for modeling these…
Investigating kernel shapes and skip connections for deep learning-based harmonic-percussive separation
Carlos Lordelo, Emmanouil Benetos, Simon Dixon +1
In this paper we propose an efficient deep learning encoder-decoder network for performing Harmonic-Percussive Source Separation (HPSS). It is shown that we are able to greatly red…
City classification from multiple real-world sound scenes
Helen L. Bear, Toni Heittola, Annamaria Mesaros +2
The majority of sound scene analysis work focuses on one of two clearly defined tasks: acoustic scene classification or sound event detection. Whilst this separation of tasks is us…
GAN-based Generation and Automatic Selection of Explanations for Neural Networks
Saumitra Mishra, Daniel Stoller, Emmanouil Benetos +2
One way to interpret trained deep neural networks (DNNs) is by inspecting characteristics that neurons in the model respond to, such as by iteratively optimising the model input (e…
Towards joint sound scene and polyphonic sound event recognition
Helen L. Bear, Ines Nolasco, Emmanouil Benetos
Acoustic Scene Classification (ASC) and Sound Event Detection (SED) are two separate tasks in the field of computational sound scene analysis. In this work, we present a new datase…
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…