Over the past decades, a particular focus is given to research on machine learning
techniques for speech processing applications. However, in the past few years, research …

Speech technologies have been developed for decades as a typical signal processing area,
while the last decade has brought a huge progress based on new machine learning …

This article proposes an encoder-decoder network model for Acoustic Scene Classification
(ASC), the task of identifying the scene of an audio recording from its acoustic signature. We …

A combined Gaussian mixture model and hidden Markov model (HMM) is developed to
distinguish between slow moving animal and human targets using mel-cepstrum …

Acoustic scene classification (ASC) using front-end timefrequency features and back-end
neural network classifiers has demonstrated good performance in recent years. However a …

Research into automated speech recognition (ASR) for the Arabic language has been
steadily increasing due to its potential for great growth. In this paper, we implemented …

Abstract Voice Disorder or Dysphonia has caught the attention of audio signal process
engineers and researchers. The efficiency of several feature extraction and classifier …

This paper explores the use of three different two-dimensional time–frequency features for
audio event classification with deep neural network back-end classifiers. The evaluations …

Prenatal stress may evoke considerable physiological consequences on the developing
poultry embryos and neonates. The present study aimed to determine prenatal auditory …

The estimation of glottal flow from a speech waveform is an essential technique used in
speech analysis and parameterisation. Significant research effort has been addressed at …