34 citations · 81 across the 18 of their papers we have counts for
13 papers · 1 filter
RADAR Challenge 2026: Robust Audio Deepfake Recognition under Media Transformations
Hieu-Thi Luong, Xuechen Liu, Ivan Kukanov +2
RADAR Challenge 2026 is an APSIPA Grand Challenge on Robust Audio Deepfake Recognition under Media Transformations, designed to simulate realistic media conditions in real-world au…
NTU-NPU System for Voice Privacy 2024 Challenge
Nikita Kuzmin, Hieu-Thi Luong, Jixun Yao +3
In this work, we describe our submissions for the Voice Privacy Challenge 2024. Rather than proposing a novel speech anonymization system, we enhance the provided baselines to meet…
Room Impulse Responses help attackers to evade Deep Fake Detection
Hieu-Thi Luong, Duc-Tuan Truong, Kong Aik Lee +1
The ASVspoof 2021 benchmark, a widely-used evaluation framework for anti-spoofing, consists of two subsets: Logical Access (LA) and Deepfake (DF), featuring samples with varied cod…
LlamaPartialSpoof: An LLM-Driven Fake Speech Dataset Simulating Disinformation Generation
Hieu-Thi Luong, Haoyang Li, Lin Zhang +2
Previous fake speech datasets were constructed from a defender's perspective to develop countermeasure (CM) systems without considering diverse motivations of attackers. To better…
Latent linguistic embedding for cross-lingual text-to-speech and voice conversion
Hieu-Thi Luong, Junichi Yamagishi
As the recently proposed voice cloning system, NAUTILUS, is capable of cloning unseen voices using untranscribed speech, we investigate the feasibility of using it to develop a uni…
NAUTILUS: a Versatile Voice Cloning System
Hieu-Thi Luong, Junichi Yamagishi
We introduce a novel speech synthesis system, called NAUTILUS, that can generate speech with a target voice either from a text input or a reference utterance of an arbitrary source…
Bootstrapping non-parallel voice conversion from speaker-adaptive text-to-speech
Hieu-Thi Luong, Junichi Yamagishi
Voice conversion (VC) and text-to-speech (TTS) are two tasks that share a similar objective, generating speech with a target voice. However, they are usually developed independentl…
A Unified Speaker Adaptation Method for Speech Synthesis using Transcribed and Untranscribed Speech with Backpropagation
Hieu-Thi Luong, Junichi Yamagishi
By representing speaker characteristic as a single fixed-length vector extracted solely from speech, we can train a neural multi-speaker speech synthesis model by conditioning the…
Training Multi-Speaker Neural Text-to-Speech Systems using Speaker-Imbalanced Speech Corpora
Hieu-Thi Luong, Xin Wang, Junichi Yamagishi +1
When the available data of a target speaker is insufficient to train a high quality speaker-dependent neural text-to-speech (TTS) system, we can combine data from multiple speakers…
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…