8 citations · 18 across the 8 of their papers we have counts for
8 papers
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…
RFWave: Multi-band Rectified Flow for Audio Waveform Reconstruction
Peng Liu, Dongyang Dai, Zhiyong Wu
Recent advancements in generative modeling have significantly enhanced the reconstruction of audio waveforms from various representations. While diffusion models are adept at this…
Cloning one's voice using very limited data in the wild
Dongyang Dai, Yuanzhe Chen, Li Chen +6
With the increasing popularity of speech synthesis products, the industry has put forward more requirements for personalized speech synthesis: (1) How to use low-resource, easily a…
Unsupervised Cross-Lingual Speech Emotion Recognition Using DomainAdversarial Neural Network
Xiong Cai, Zhiyong Wu, Kuo Zhong +3
By using deep learning approaches, Speech Emotion Recog-nition (SER) on a single domain has achieved many excellentresults. However, cross-domain SER is still a challenging taskdue…
Emotion controllable speech synthesis using emotion-unlabeled dataset with the assistance of cross-domain speech emotion recognition
Xiong Cai, Dongyang Dai, Zhiyong Wu +3
Neural text-to-speech (TTS) approaches generally require a huge number of high quality speech data, which makes it difficult to obtain such a dataset with extra emotion labels. In…