In a world that has rapidly transformed through the advent of artificial intelligence (AI), our
systematic review, guided by the PRISMA protocol, investigates a decade of AI research …

In recent years, convolutional neural networks (CNNs) have shown great performance in
various fields such as image classification, pattern recognition, and multi-media …

Nowadays, deep learning is a current and a stimulating field of machine learning. Deep
learning is the most effective, supervised, time and cost efficient machine learning approach …

Since the proposal of a fast learning algorithm for deep belief networks in 2006, the deep
learning techniques have drawn ever-increasing research interests because of their …

We introduce the Merlin speech synthesis toolkit for neural network-based speech synthesis.
The system takes linguistic features as input, and employs neural networks to predict …

Abstract Objects make distinctive sounds when they are hit or scratched. These sounds
reveal aspects of an object's material properties, as well as the actions that produced them …

Voice transformation (VT) aims to change one or more aspects of a speech signal while
preserving linguistic information. A subset of VT, Voice conversion (VC) specifically aims to …

Nowadays speech synthesis or text to speech (TTS), an ability of system to produce human
like natural sounding voice from the written text, is gaining popularity in the field of speech …

A method for statistical parametric speech synthesis incorporating generative adversarial
networks (GANs) is proposed. Although powerful deep neural networks techniques can be …

Deep learning of artificial neural networks has become the de facto standard approach to
solving data analysis problems in virtually all fields of science and engineering. Also in …