A review on generative adversarial networks: Algorithms, theory, and applications
Generative adversarial networks (GANs) have recently become a hot research topic;
however, they have been studied since 2014, and a large number of algorithms have been …
however, they have been studied since 2014, and a large number of algorithms have been …
A survey of deep learning: Platforms, applications and emerging research trends
WG Hatcher, W Yu - IEEE access, 2018 - ieeexplore.ieee.org
Deep learning has exploded in the public consciousness, primarily as predictive and
analytical products suffuse our world, in the form of numerous human-centered smart-world …
analytical products suffuse our world, in the form of numerous human-centered smart-world …
High fidelity speech synthesis with adversarial networks
Generative adversarial networks have seen rapid development in recent years and have led
to remarkable improvements in generative modelling of images. However, their application …
to remarkable improvements in generative modelling of images. However, their application …
Stargan-vc: Non-parallel many-to-many voice conversion using star generative adversarial networks
This paper proposes a method that allows non-parallel many-to-many voice conversion (VC)
by using a variant of a generative adversarial network (GAN) called StarGAN. Our method …
by using a variant of a generative adversarial network (GAN) called StarGAN. Our method …
An intelligent fault diagnosis model based on deep neural network for few-shot fault diagnosis
C Wang, Z Xu - Neurocomputing, 2021 - Elsevier
The most existing deep neural networks (DNN)-based methods for fault diagnosis only focus
on prediction accuracy without considering the limitation of labeled sample size. In practical …
on prediction accuracy without considering the limitation of labeled sample size. In practical …
A small-sample wind turbine fault detection method with synthetic fault data using generative adversarial nets
The limited fault information caused by small fault data samples is a major problem in wind
turbine (WT) fault detection. This paper proposes a small-sample WT fault detection method …
turbine (WT) fault detection. This paper proposes a small-sample WT fault detection method …
Speech analysis for health: Current state-of-the-art and the increasing impact of deep learning
Due to the complex and intricate nature associated with their production, the acoustic-
prosodic properties of a speech signal are modulated with a range of health related effects …
prosodic properties of a speech signal are modulated with a range of health related effects …
A survey on voice assistant security: Attacks and countermeasures
Voice assistants (VA) have become prevalent on a wide range of personal devices such as
smartphones and smart speakers. As companies build voice assistants with extra …
smartphones and smart speakers. As companies build voice assistants with extra …
[PDF][PDF] WaveNet Vocoder with Limited Training Data for Voice Conversion.
This paper investigates the approaches of building WaveNet vocoders with limited training
data for voice conversion (VC). Current VC systems using statistical acoustic models always …
data for voice conversion (VC). Current VC systems using statistical acoustic models always …
Advances in anti-spoofing: from the perspective of ASVspoof challenges
In recent years, automatic speaker verification (ASV) is used extensively for voice biometrics.
This leads to an increased interest to secure these voice biometric systems for real-world …
This leads to an increased interest to secure these voice biometric systems for real-world …