40 citations · 93 across the 11 of their papers we have counts for
11 papers
A Method for Identifying Origin of Digital Images Using a Convolution Neural Network
Rong Huang, Fuming Fang, Huy H. Nguyen +2
The rapid development of deep learning techniques has created new challenges in identifying the origin of digital images because generative adversarial networks and variational aut…
Security of Facial Forensics Models Against Adversarial Attacks
Rong Huang, Fuming Fang, Huy H. Nguyen +2
Deep neural networks (DNNs) have been used in digital forensics to identify fake facial images. We investigated several DNN-based forgery forensics models (FFMs) to examine whether…
Zero-Shot Multi-Speaker Text-To-Speech with State-of-the-art Neural Speaker Embeddings
Erica Cooper, Cheng-I Lai, Yusuke Yasuda +4
While speaker adaptation for end-to-end speech synthesis using speaker embeddings can produce good speaker similarity for speakers seen during training, there remains a gap for zer…
Generating Sentiment-Preserving Fake Online Reviews Using Neural Language Models and Their Human- and Machine-based Detection
David Ifeoluwa Adelani, Haotian Mai, Fuming Fang +3
Advanced neural language models (NLMs) are widely used in sequence generation tasks because they are able to produce fluent and meaningful sentences. They can also be used to gener…
Multi-task Learning For Detecting and Segmenting Manipulated Facial Images and Videos
Huy H. Nguyen, Fuming Fang, Junichi Yamagishi +1
Detecting manipulated images and videos is an important topic in digital media forensics. Most detection methods use binary classification to determine the probability of a query b…
Speaker Anonymization Using X-vector and Neural Waveform Models
Fuming Fang, Xin Wang, Junichi Yamagishi +4
The social media revolution has produced a plethora of web services to which users can easily upload and share multimedia documents. Despite the popularity and convenience of such…
Joint training framework for text-to-speech and voice conversion using multi-source Tacotron and WaveNet
Mingyang Zhang, Xin Wang, Fuming Fang +2
We investigated the training of a shared model for both text-to-speech (TTS) and voice conversion (VC) tasks. We propose using an extended model architecture of Tacotron, that is a…
Audiovisual speaker conversion: jointly and simultaneously transforming facial expression and acoustic characteristics
Fuming Fang, Xin Wang, Junichi Yamagishi +1
An audiovisual speaker conversion method is presented for simultaneously transforming the facial expressions and voice of a source speaker into those of a target speaker. Transform…
Transforming acoustic characteristics to deceive playback spoofing countermeasures of speaker verification systems
Fuming Fang, Junichi Yamagishi, Isao Echizen +2
Automatic speaker verification (ASV) systems use a playback detector to filter out playback attacks and ensure verification reliability. Since current playback detection models are…
High-quality nonparallel voice conversion based on cycle-consistent adversarial network
Fuming Fang, Junichi Yamagishi, Isao Echizen +1
Although voice conversion (VC) algorithms have achieved remarkable success along with the development of machine learning, superior performance is still difficult to achieve when u…
Can we steal your vocal identity from the Internet?: Initial investigation of cloning Obama's voice using GAN, WaveNet and low-quality found data
Jaime Lorenzo-Trueba, Fuming Fang, Xin Wang +3
Thanks to the growing availability of spoofing databases and rapid advances in using them, systems for detecting voice spoofing attacks are becoming more and more capable, and erro…