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pro vyhledávání: '"Liu, XiaoQian"'
Autor:
Liu, Xiaoqian, Du, Yangfan, Wang, Jianjin, Ge, Yuan, Xu, Chen, Xiao, Tong, Chen, Guocheng, Zhu, Jingbo
Simultaneous Speech Translation (SimulST) involves generating target language text while continuously processing streaming speech input, presenting significant real-time challenges. Multi-task learning is often employed to enhance SimulST performance
Externí odkaz:
http://arxiv.org/abs/2409.15911
Autor:
Xu, Chen, Wang, Jie, Liu, Xiaoqian, Dong, Qianqian, Zhang, Chunliang, Xiao, Tong, Zhu, Jingbo, Man, Dapeng, Yang, Wu
Speech-to-text (S2T) generation systems frequently face challenges in low-resource scenarios, primarily due to the lack of extensive labeled datasets. One emerging solution is constructing virtual training samples by interpolating inputs and labels,
Externí odkaz:
http://arxiv.org/abs/2406.15846
Autor:
Liu, Xiaoqian, Hu, Guoqiang, Du, Yangfan, He, Erfeng, Luo, Yingfeng, Xu, Chen, Xiao, Tong, Zhu, Jingbo
Simultaneous speech translation (SimulST) is a demanding task that involves generating translations in real-time while continuously processing speech input. This paper offers a comprehensive overview of the recent developments in SimulST research, fo
Externí odkaz:
http://arxiv.org/abs/2406.00497
Decision making demands intricate interplay between perception, memory, and reasoning to discern optimal policies. Conventional approaches to decision making face challenges related to low sample efficiency and poor generalization. In contrast, found
Externí odkaz:
http://arxiv.org/abs/2405.17009
Publikováno v:
JMIR mHealth and uHealth, Vol 9, Iss 1, p e19046 (2021)
BackgroundAs smartphone has been widely used, understanding how depression correlates with social behavior on smartphones can be beneficial for early diagnosis of depression. An enormous amount of research relied on self-report questionnaires, which
Externí odkaz:
https://doaj.org/article/0cc7146876f64c628b1f395ed6d4e322
Publikováno v:
Journal of Medical Internet Research, Vol 22, Iss 12, p e24775 (2020)
BackgroundDuring the COVID-19 pandemic, residential lockdowns were implemented in numerous cities in China to contain the rapid spread of the disease. Although these stringent regulations effectively slowed the spread of COVID-19, they may have posed
Externí odkaz:
https://doaj.org/article/b156ec2868b4437a9f75deedf439583e
Publikováno v:
Journal of Medical Internet Research, Vol 22, Iss 4, p e16470 (2020)
BackgroundStigma related to schizophrenia is considered to be the primary focus of antistigma campaigns. Accurate and efficient detection of stigma toward schizophrenia in mass media is essential for the development of targeted antistigma interventio
Externí odkaz:
https://doaj.org/article/c9f3c92021fa440180eb6c75f57f375d
Decision-making is a dynamic process requiring perception, memory, and reasoning to make choices and find optimal policies. Traditional approaches to decision-making suffer from sample efficiency and generalization, while large-scale self-supervised
Externí odkaz:
http://arxiv.org/abs/2401.00031
Continual learning addresses the problem of continuously acquiring and transferring knowledge without catastrophic forgetting of old concepts. While humans achieve continual learning via diverse neurocognitive mechanisms, there is a mismatch between
Externí odkaz:
http://arxiv.org/abs/2312.03309