9 citations · 10 across the 7 of their papers we have counts for
7 papers
EGAM: Extended Graph Attention Model for Solving Routing Problems
Licheng Wang, Yuzi Yan, Mingtao Huang +1
Neural combinatorial optimization (NCO) solvers, implemented with graph neural networks (GNNs), have introduced new approaches for solving routing problems. Trained with reinforcem…
Distributed Policy Gradient for Linear Quadratic Networked Control with Limited Communication Range
Yuzi Yan, Yuan Shen
This paper proposes a scalable distributed policy gradient method and proves its convergence to near-optimal solution in multi-agent linear quadratic networked systems. The agents…
Mixed-Phoneme BERT: Improving BERT with Mixed Phoneme and Sup-Phoneme Representations for Text to Speech
Guangyan Zhang, Kaitao Song, Xu Tan +8
Recently, leveraging BERT pre-training to improve the phoneme encoder in text to speech (TTS) has drawn increasing attention. However, the works apply pre-training with character-b…
Relative Distributed Formation and Obstacle Avoidance with Multi-agent Reinforcement Learning
Yuzi Yan, Xiaoxiang Li, Xinyou Qiu +4
Multi-agent formation as well as obstacle avoidance is one of the most actively studied topics in the field of multi-agent systems. Although some classic controllers like model pre…
Full Attention Bidirectional Deep Learning Structure for Single Channel Speech Enhancement
Yuzi Yan, Wei-Qiang Zhang, Michael T. Johnson
As the cornerstone of other important technologies, such as speech recognition and speech synthesis, speech enhancement is a critical area in audio signal processing. In this paper…
AdaSpeech 3: Adaptive Text to Speech for Spontaneous Style
Yuzi Yan, Xu Tan, Bohan Li +6
While recent text to speech (TTS) models perform very well in synthesizing reading-style (e.g., audiobook) speech, it is still challenging to synthesize spontaneous-style speech (e…
AdaSpeech 2: Adaptive Text to Speech with Untranscribed Data
Yuzi Yan, Xu Tan, Bohan Li +4
Text to speech (TTS) is widely used to synthesize personal voice for a target speaker, where a well-trained source TTS model is fine-tuned with few paired adaptation data (speech a…