84 citations · 183 across the 32 of their papers we have counts for
11 papers · 1 filter
learning discriminative features from spectrograms using center loss for speech emotion recognition
Dongyang Dai, Zhiyong Wu, Runnan Li +3
Identifying the emotional state from speech is essential for the natural interaction of the machine with the speaker. However, extracting effective features for emotion recognition…
Disambiguation of Chinese Polyphones in an End-to-End Framework with Semantic Features Extracted by Pre-trained BERT
Dongyang Dai, Zhiyong Wu, Shiyin Kang +5
Grapheme-to-phoneme (G2P) conversion serves as an essential component in Chinese Mandarin text-to-speech (TTS) system, where polyphone disambiguation is the core issue. In this pap…
A Hierarchical Regression Chain Framework for Affective Vocal Burst Recognition
Jinchao Li, Xixin Wu, Kaitao Song +3
As a common way of emotion signaling via non-linguistic vocalizations, vocal burst (VB) plays an important role in daily social interaction. Understanding and modeling human vocal…
Leveraging Pretrained Representations with Task-related Keywords for Alzheimer's Disease Detection
Jinchao Li, Kaitao Song, Junan Li +5
With the global population aging rapidly, Alzheimer's disease (AD) is particularly prominent in older adults, which has an insidious onset and leads to a gradual, irreversible dete…
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…
Improved End-to-End Dysarthric Speech Recognition via Meta-learning Based Model Re-initialization
Disong Wang, Jianwei Yu, Xixin Wu +3
Dysarthric speech recognition is a challenging task as dysarthric data is limited and its acoustics deviate significantly from normal speech. Model-based speaker adaptation is a pr…
Any-to-Many Voice Conversion with Location-Relative Sequence-to-Sequence Modeling
Songxiang Liu, Yuewen Cao, Disong Wang +3
This paper proposes an any-to-many location-relative, sequence-to-sequence (seq2seq), non-parallel voice conversion approach, which utilizes text supervision during training. In th…
Investigating Robustness of Adversarial Samples Detection for Automatic Speaker Verification
Xu Li, Na Li, Jinghua Zhong +5
Recently adversarial attacks on automatic speaker verification (ASV) systems attracted widespread attention as they pose severe threats to ASV systems. However, methods to defend a…
Bayesian x-vector: Bayesian Neural Network based x-vector System for Speaker Verification
Xu Li, Jinghua Zhong, Jianwei Yu +4
Speaker verification systems usually suffer from the mismatch problem between training and evaluation data, such as speaker population mismatch, the channel and environment variati…
Adversarial Attacks on GMM i-vector based Speaker Verification Systems
Xu Li, Jinghua Zhong, Xixin Wu +3
This work investigates the vulnerability of Gaussian Mixture Model (GMM) i-vector based speaker verification systems to adversarial attacks, and the transferability of adversarial…
Maximizing Mutual Information for Tacotron
Peng Liu, Xixin Wu, Shiyin Kang +3
End-to-end speech synthesis methods already achieve close-to-human quality performance. However compared to HMM-based and NN-based frame-to-frame regression methods, they are prone…