Generative adversarial networks (GAN) have recently been shown to be
eff...
Although large annotated sleep databases are publicly available, and mig...
Many sleep studies suffer from the problem of insufficient data to fully...
Acoustic scenes are rich and redundant in their content. In this work, w...
Due to the variability in characteristics of audio scenes, some can natu...
We propose a multi-label multi-task framework based on a convolutional
r...
Automatic sleep staging has been often treated as a simple classificatio...
Sleep staging plays an important role in assessment and treatment of sle...
This paper presents a methodology for early detection of audio events fr...
This report presents our audio event detection system submitted for Task...
We trained a deep all-convolutional neural network with masked global po...
This report describes our submissions to Task2 and Task3 of the DCASE 20...
We describe in this report our audio scene recognition system submitted ...
We present in this paper an efficient approach for acoustic scene
classi...
We introduce a new learned descriptor for audio signals which is efficie...
We present in this paper a simple, yet efficient convolutional neural ne...
Recognizing acoustic events is an intricate problem for a machine and an...