Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Le, Chenyang"'
Autor:
Le, Chenyang, Qian, Yao, Wang, Dongmei, Zhou, Long, Liu, Shujie, Wang, Xiaofei, Yousefi, Midia, Qian, Yanmin, Li, Jinyu, Zhao, Sheng, Zeng, Michael
There is a rising interest and trend in research towards directly translating speech from one language to another, known as end-to-end speech-to-speech translation. However, most end-to-end models struggle to outperform cascade models, i.e., a pipeli
Externí odkaz:
http://arxiv.org/abs/2405.17809
Autor:
Le, Chenyang, Qian, Yao, Zhou, Long, Liu, Shujie, Qian, Yanmin, Zeng, Michael, Huang, Xuedong
Joint speech-language training is challenging due to the large demand for training data and GPU consumption, as well as the modality gap between speech and language. We present ComSL, a speech-language model built atop a composite architecture of pub
Externí odkaz:
http://arxiv.org/abs/2305.14838
Autor:
Wen, Ying, Wan, Ziyu, Zhou, Ming, Hou, Shufang, Cao, Zhe, Le, Chenyang, Chen, Jingxiao, Tian, Zheng, Zhang, Weinan, Wang, Jun
The pervasive uncertainty and dynamic nature of real-world environments present significant challenges for the widespread implementation of machine-driven Intelligent Decision-Making (IDM) systems. Consequently, IDM should possess the ability to cont
Externí odkaz:
http://arxiv.org/abs/2212.12669
With the increasing popularity and accessibility of high dynamic range (HDR) photography, tone mapping operators (TMOs) for dynamic range compression are practically demanding. In this paper, we develop a two-stage neural network-based TMO that is se
Externí odkaz:
http://arxiv.org/abs/2206.09146
Autor:
Meng, Linghui, Wen, Muning, Yang, Yaodong, Le, Chenyang, Li, Xiyun, Zhang, Weinan, Wen, Ying, Zhang, Haifeng, Wang, Jun, Xu, Bo
Offline reinforcement learning leverages previously-collected offline datasets to learn optimal policies with no necessity to access the real environment. Such a paradigm is also desirable for multi-agent reinforcement learning (MARL) tasks, given th
Externí odkaz:
http://arxiv.org/abs/2112.02845
We describe a deep high-dynamic-range (HDR) image tone mapping operator that is computationally efficient and perceptually optimized. We first decompose an HDR image into a normalized Laplacian pyramid, and use two deep neural networks (DNNs) to esti
Externí odkaz:
http://arxiv.org/abs/2109.00180
Autor:
Meng, Linghui, Wen, Muning, Le, Chenyang, Li, Xiyun, Xing, Dengpeng, Zhang, Weinan, Wen, Ying, Zhang, Haifeng, Wang, Jun, Yang, Yaodong, Xu, Bo
Publikováno v:
Machine Intelligence Research; April 2023, Vol. 20 Issue: 2 p233-248, 16p