1.8k citations · 3.5k across the 130 of their papers we have counts for
24 papers · 1 filter
Identifying Computer-Translated Paragraphs using Coherence Features
Hoang-Quoc Nguyen-Son, Ngoc-Dung T. Tieu, Huy H. Nguyen +2
We have developed a method for extracting the coherence features from a paragraph by matching similar words in its sentences. We conducted an experiment with a parallel German corp…
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…
Attentive Filtering Networks for Audio Replay Attack Detection
Cheng-I Lai, Alberto Abad, Korin Richmond +3
An attacker may use a variety of techniques to fool an automatic speaker verification system into accepting them as a genuine user. Anti-spoofing methods meanwhile aim to make the…
Waveform generation for text-to-speech synthesis using pitch-synchronous multi-scale generative adversarial networks
Lauri Juvela, Bajibabu Bollepalli, Junichi Yamagishi +1
The state-of-the-art in text-to-speech synthesis has recently improved considerably due to novel neural waveform generation methods, such as WaveNet. However, these methods suffer…
STFT spectral loss for training a neural speech waveform model
Shinji Takaki, Toru Nakashika, Xin Wang +1
This paper proposes a new loss using short-time Fourier transform (STFT) spectra for the aim of training a high-performance neural speech waveform model that predicts raw continuou…
Capsule-Forensics: Using Capsule Networks to Detect Forged Images and Videos
Huy H. Nguyen, Junichi Yamagishi, Isao Echizen
Recent advances in media generation techniques have made it easier for attackers to create forged images and videos. State-of-the-art methods enable the real-time creation of a for…
Investigation of enhanced Tacotron text-to-speech synthesis systems with self-attention for pitch accent language
Yusuke Yasuda, Xin Wang, Shinji Takaki +1
End-to-end speech synthesis is a promising approach that directly converts raw text to speech. Although it was shown that Tacotron2 outperforms classical pipeline systems with rega…
Neural source-filter-based waveform model for statistical parametric speech synthesis
Xin Wang, Shinji Takaki, Junichi Yamagishi
Neural waveform models such as the WaveNet are used in many recent text-to-speech systems, but the original WaveNet is quite slow in waveform generation because of its autoregressi…
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…
MesoNet: a Compact Facial Video Forgery Detection Network
Darius Afchar, Vincent Nozick, Junichi Yamagishi +1
This paper presents a method to automatically and efficiently detect face tampering in videos, and particularly focuses on two recent techniques used to generate hyper-realistic fo…
Multimodal speech synthesis architecture for unsupervised speaker adaptation
Hieu-Thi Luong, Junichi Yamagishi
This paper proposes a new architecture for speaker adaptation of multi-speaker neural-network speech synthesis systems, in which an unseen speaker's voice can be built using a rela…
Investigating accuracy of pitch-accent annotations in neural network-based speech synthesis and denoising effects
Hieu-Thi Luong, Xin Wang, Junichi Yamagishi +1
We investigated the impact of noisy linguistic features on the performance of a Japanese speech synthesis system based on neural network that uses WaveNet vocoder. We compared an i…
Wasserstein GAN and Waveform Loss-based Acoustic Model Training for Multi-speaker Text-to-Speech Synthesis Systems Using a WaveNet Vocoder
Yi Zhao, Shinji Takaki, Hieu-Thi Luong +3
Recent neural networks such as WaveNet and sampleRNN that learn directly from speech waveform samples have achieved very high-quality synthetic speech in terms of both naturalness…
Scaling and bias codes for modeling speaker-adaptive DNN-based speech synthesis systems
Hieu-Thi Luong, Junichi Yamagishi
Most neural-network based speaker-adaptive acoustic models for speech synthesis can be categorized into either layer-based or input-code approaches. Although both approaches have t…
Deep Encoder-Decoder Models for Unsupervised Learning of Controllable Speech Synthesis
Gustav Eje Henter, Jaime Lorenzo-Trueba, Xin Wang +1
Generating versatile and appropriate synthetic speech requires control over the output expression separate from the spoken text. Important non-textual speech variation is seldom an…
Speaker-independent raw waveform model for glottal excitation
Lauri Juvela, Vassilis Tsiaras, Bajibabu Bollepalli +3
Recent speech technology research has seen a growing interest in using WaveNets as statistical vocoders, i.e., generating speech waveforms from acoustic features. These models have…
Transformation on Computer-Generated Facial Image to Avoid Detection by Spoofing Detector
Huy H. Nguyen, Ngoc-Dung T. Tieu, Hoang-Quoc Nguyen-Son +2
Making computer-generated (CG) images more difficult to detect is an interesting problem in computer graphics and security. While most approaches focus on the image rendering phase…
The Voice Conversion Challenge 2018: Promoting Development of Parallel and Nonparallel Methods
Jaime Lorenzo-Trueba, Junichi Yamagishi, Tomoki Toda +4
We present the Voice Conversion Challenge 2018, designed as a follow up to the 2016 edition with the aim of providing a common framework for evaluating and comparing different stat…
Speech waveform synthesis from MFCC sequences with generative adversarial networks
Lauri Juvela, Bajibabu Bollepalli, Xin Wang +4
This paper proposes a method for generating speech from filterbank mel frequency cepstral coefficients (MFCC), which are widely used in speech applications, such as ASR, but are ge…
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…
t-DCF: a Detection Cost Function for the Tandem Assessment of Spoofing Countermeasures and Automatic Speaker Verification
Tomi Kinnunen, Kong Aik Lee, Hector Delgado +5
The ASVspoof challenge series was born to spearhead research in anti-spoofing for automatic speaker verification (ASV). The two challenge editions in 2015 and 2017 involved the ass…
A Spoofing Benchmark for the 2018 Voice Conversion Challenge: Leveraging from Spoofing Countermeasures for Speech Artifact Assessment
Tomi Kinnunen, Jaime Lorenzo-Trueba, Junichi Yamagishi +4
Voice conversion (VC) aims at conversion of speaker characteristic without altering content. Due to training data limitations and modeling imperfections, it is difficult to achieve…
Complex-Valued Restricted Boltzmann Machine for Direct Speech Parameterization from Complex Spectra
Toru Nakashika, Shinji Takaki, Junichi Yamagishi
This paper describes a novel energy-based probabilistic distribution that represents complex-valued data and explains how to apply it to direct feature extraction from complex-valu…
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…