CASIA OpenIR

浏览/检索结果: 共5条,第1-5条 帮助

限定条件                    
已选(0)清除 条数/页:   排序方式:
AccPen: Using Smartphone with Accelerometer to Interact as Pen 会议论文
, Montreal, QC, Canada, April 21–22, 2018
作者:  Junjun Fan;  Run Su;  Yuansong Sun;  Peiyu Guan;  Yujie Chen;  Jie Liu;  Feng Tian
Adobe PDF(722Kb)  |  收藏  |  浏览/下载:173/46  |  提交时间:2022/06/20
Towards end-to-end speech recognition for Chinese Mandarin using long short-term memory recurrent neural networks 会议论文
INTERSPEECH 2015 emphasizes an interdisciplinary approach covering all aspects of speech science and technology spanning basic theories to applications. In addition to regular oral and poster sessions, the conference will also feature plenary talks by internationally renowned experts, tutorials, special sessions, show & tell sessions, and exhibits. A number of satellite events will take place immediately before and after the conference., 德国, 2015年
作者:  Li J(李杰);  Zhang H(张恒);  Cai XY(蔡新元);  Xu B(徐波)
收藏  |  浏览/下载:65/0  |  提交时间:2020/10/27
Towards End-to-End Speech Recognition for Chinese Mandarin using Long Short-Term Memory Recurrent Neural Networks 会议论文
Interspeech 2015, Dersen,German, 2016.9.6-2016.9.10
作者:  Jie Li;  Heng Zhang;  Xinyuan Cai;  Bo Xu
收藏  |  浏览/下载:105/0  |  提交时间:2020/10/27
Long Short-term Memory  End-to-end  Connectionist Temporal Classification  Speech Recognition  
Multilingual Tandem Bottleneck Feature For Language Identification 会议论文
Interspeech2015, Dresden,German, 2016.9.6-2016.9.10
作者:  Wang Geng;  Jie Li,;  Shanshan Zhang;  Xinyuan Cai;  Bo Xu;  Xinyuan.Cai
收藏  |  浏览/下载:136/0  |  提交时间:2020/10/27
Language Identification  Deep Bottleneck Feature  Tandem Feature  Multi-deep Feature  Multi-training Procedure.  
Investigating Gated Recurrent Neural Networks for Acoustic Modeling 会议论文
, Tianjin, China, October 17-20
作者:  Zhao, Yuanyuan;  Li, Jie;  Xu, Shuang;  Xu, Bo;  Yuanyuan Zhao
收藏  |  浏览/下载:41/0  |  提交时间:2020/10/27
Gated Recurrent Neural Networks  Long Short-term Memory Unit  Gated Recurrent Neural Networks  Long Short-term Memory Projected Unit