5 citations · 10 across the 4 of their papers we have counts for
5 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…
A Discourse-level Multi-scale Prosodic Model for Fine-grained Emotion Analysis
Xianhao Wei, Jia Jia, Xiang Li +2
This paper explores predicting suitable prosodic features for fine-grained emotion analysis from the discourse-level text. To obtain fine-grained emotional prosodic features as pre…
VAST: Vivify Your Talking Avatar via Zero-Shot Expressive Facial Style Transfer
Liyang Chen, Zhiyong Wu, Runnan Li +4
Current talking face generation methods mainly focus on speech-lip synchronization. However, insufficient investigation on the facial talking style leads to a lifeless and monotono…
QPGesture: Quantization-Based and Phase-Guided Motion Matching for Natural Speech-Driven Gesture Generation
Sicheng Yang, Zhiyong Wu, Minglei Li +4
Speech-driven gesture generation is highly challenging due to the random jitters of human motion. In addition, there is an inherent asynchronous relationship between human speech a…
DiffuseStyleGesture: Stylized Audio-Driven Co-Speech Gesture Generation with Diffusion Models
Sicheng Yang, Zhiyong Wu, Minglei Li +5
The art of communication beyond speech there are gestures. The automatic co-speech gesture generation draws much attention in computer animation. It is a challenging task due to th…