Although it is typically expected that using a large amount of labeled training data would
lead to improve performance in deep learning, it is generally difficult to obtain such …

This report describes the 4 submissions for Task 1 (Audio scene classification) of the
DCASE-2016 challenge of the CP-JKU team. We propose 4 different approaches for Audio …

The paper presents a novel automatic speaker age and gender identification approach
which combines seven different methods at both acoustic and prosodic levels to improve the …

The paper presents a set of experiments on pathological voice detection over the
Saarbrücken Voice Database (SVD) by using the MultiFocal toolkit for a discriminative …

In this paper, the Brno University of Technology (BUT) team submissions for Task 1
(Acoustic Scene Classification, ASC) of the DCASE-2018 challenge are described. Also, the …

Objective Atherosclerotic coronary artery disease (CAD) detection through a simple, non-
invasive approach will be useful in point-of-care diagnosis. Though numerous studies have …

This paper presents a simplified and supervised i-vector modeling approach with
applications to robust and efficient language identification and speaker verification. First, by …

Deep learning methods for language recognition have achieved promising performance.
However, most of the studies focus on frameworks for single types of acoustic features and …

Acoustic scene classification (ASC) is an audio signal processing task where mel-scaled
spectral features are widely used by researchers. These features, considered de facto …

Automatic speaker verification (ASV) systems are vulnerable to various types of spoofing
attacks such as speech synthesis, voice conversion and replay attacks. Recent research has …