84 citations · 183 across the 32 of their papers we have counts for
9 papers · 1 filter
Towards High-Quality Neural TTS for Low-Resource Languages by Learning Compact Speech Representations
Haohan Guo, Fenglong Xie, Xixin Wu +2
This paper aims to enhance low-resource TTS by reducing training data requirements using compact speech representations. A Multi-Stage Multi-Codebook (MSMC) VQ-GAN is trained to le…
Disentangled Speech Representation Learning for One-Shot Cross-lingual Voice Conversion Using -VAE
Hui Lu, Disong Wang, Xixin Wu +3
We propose an unsupervised learning method to disentangle speech into content representation and speaker identity representation. We apply this method to the challenging one-shot c…
A Multi-Stage Multi-Codebook VQ-VAE Approach to High-Performance Neural TTS
Haohan Guo, Fenglong Xie, Frank K. Soong +2
We propose a Multi-Stage, Multi-Codebook (MSMC) approach to high-performance neural TTS synthesis. A vector-quantized, variational autoencoder (VQ-VAE) based feature analyzer is us…
Tackling Spoofing-Aware Speaker Verification with Multi-Model Fusion
Haibin Wu, Jiawen Kang, Lingwei Meng +5
Recent years have witnessed the extraordinary development of automatic speaker verification (ASV). However, previous works show that state-of-the-art ASV models are seriously vulne…
Exploring linguistic feature and model combination for speech recognition based automatic AD detection
Yi Wang, Tianzi Wang, Zi Ye +5
Early diagnosis of Alzheimer's disease (AD) is crucial in facilitating preventive care and delay progression. Speech based automatic AD screening systems provide a non-intrusive an…
Neural Architecture Search for Speech Emotion Recognition
Xixin Wu, Shoukang Hu, Zhiyong Wu +2
Deep neural networks have brought significant advancements to speech emotion recognition (SER). However, the architecture design in SER is mainly based on expert knowledge and empi…
Spoofing-Aware Speaker Verification by Multi-Level Fusion
Haibin Wu, Lingwei Meng, Jiawen Kang +5
Recently, many novel techniques have been introduced to deal with spoofing attacks, and achieve promising countermeasure (CM) performances. However, these works only take the stand…
A Multi-Scale Time-Frequency Spectrogram Discriminator for GAN-based Non-Autoregressive TTS
Haohan Guo, Hui Lu, Xixin Wu +1
The generative adversarial network (GAN) has shown its outstanding capability in improving Non-Autoregressive TTS (NAR-TTS) by adversarially training it with an extra model that di…
Estimating the Uncertainty in Emotion Class Labels with Utterance-Specific Dirichlet Priors
Wen Wu, Chao Zhang, Xixin Wu +1
Emotion recognition is a key attribute for artificial intelligence systems that need to naturally interact with humans. However, the task definition is still an open problem due to…