中文版 | English

在结果中检索

CASIA OpenIR
（本次检索基于用户作品认领结果）

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：
Gated Recurrent Fusion With Joint Training Framework for Robust End-to-End Speech Recognition 期刊论文
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2021, 期号: 29, 页码: 198-209
作者:  Fan, Cunhang;  Yi, Jiangyan;  Tao, Jianhua;  Tian, Zhengkun;  Liu, Bin;  Wen, Zhengqi
Adobe PDF(2534Kb)  |  收藏  |  浏览/下载：403/51  |  提交时间：2021/03/08
Speech enhancement  Speech recognition  Training  Noise measurement  Logic gates  Acoustic distortion  Task analysis  Gated recurrent fusion  robust end-to-end speech recognition  speech distortion  speech enhancement  speech transformer  
Speech Enhancement Based on Analysis-Synthesis Framework with Improved Parameter Domain Enhancement 期刊论文
JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, 2016, 卷号: 82, 期号: 2, 页码: 141-150
作者:  Liu, Bin;  Tao, Jianhua;  Wen, Zhengqi;  Mo, Fuyuan;  Bin Liu
收藏  |  浏览/下载：57/0  |  提交时间：2020/10/27
Analysis-synthesis Framework  Multi-band Summary Correlogram  Denoising Autoencoder  Speech Enhancement  Speech Coding  
Investigating Deep Neural Network Adaptation for Generating Exclamatory and Interrogative Speech in Mandarin 期刊论文
JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, 2018, 卷号: 90, 期号: 7, 页码: 1039-1052
作者:  Zheng, Yibin;  Li, Ya;  Wen, Zhengqi;  Liu, Bin;  Tao, Jianhua;  Jianhua Tao
收藏  |  浏览/下载：116/0  |  提交时间：2020/10/27
Speech Synthesis  Excitation Parameters  Deep Neural Network Adaptation  Exclamatory Speech  Interrogative Speech  
CTC Regularized Model Adaptation for Improving LSTM RNN Based Multi-Accent Mandarin Speech Recognition 期刊论文
JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, 2018, 卷号: 90, 期号: 7, 页码: 985-997
作者:  Jiangyan Yi;  Zhengqi Wen;  Jianhua Tao;  Hao Ni;  Bin Liu
浏览  |  Adobe PDF(1416Kb)  |  收藏  |  浏览/下载：149/56  |  提交时间：2020/10/22
multi-accent, Mandarin speech recognition,LSTM-RNN-CTC, model adaptation, CTC regularization  
End-to-End Post-Filter for Speech Separation With Deep Attention Fusion Features 期刊论文
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2020, 卷号: 28, 期号: 28, 页码: 1303-1314
作者:  Fan, Cunhang;  Tao, Jianhua;  Liu, Bin;  Yi, Jiangyan;  Wen, Zhengqi;  Liu, Xuefei
Adobe PDF(1344Kb)  |  收藏  |  浏览/下载：308/65  |  提交时间：2020/06/22
Feature extraction  Training  Interference  Speech enhancement  Clustering algorithms  Spectrogram  Speech separation  end-to-end post-filter  deep attention fusion features  deep clustering  permutation invariant training