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CASIA OpenIR
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NeuralDPS: Neural Deterministic Plus Stochastic Model With Multiband Excitation for Noise-Controllable Waveform Generation 期刊论文
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2022, 卷号: 30, 页码: 865-878
作者:  Wang, Tao;  Fu, Ruibo;  Yi, Jiangyan;  Tao, Jianhua;  Wen, Zhengqi
收藏  |  浏览/下载：271/0  |  提交时间：2022/06/06
Vocoders  Stochastic processes  Neural networks  Speech processing  Signal to noise ratio  Acoustics  Speech enhancement  Vocoder  speech synthesis  deterministic plus stochastic  multiband excitation  noise control  
Deep Time Delay Neural Network for Speech Enhancement with Full Data Learning 会议论文
, Hong Kong, 24-27 Jan. 2021
作者:  Fan, Cunhang;  Liu, Bin;  Tao, Jianhua;  Yi, Jiangyan;  Wen, Zhengqi;  Song, Leichao
Adobe PDF(934Kb)  |  收藏  |  浏览/下载：235/56  |  提交时间：2021/06/01
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：409/52  |  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  
Pitch-Scaled Spectrum Based Excitation Model for HMM-based Speech Synthesis 期刊论文
JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, 2014, 卷号: 74, 期号: 3, 页码: 423-435
作者:  Wen, Zhengqi;  Tao, Jianhua;  Pan, Shifeng;  Wang, Yang;  Zhengqi Wen
收藏  |  浏览/下载：23/0  |  提交时间：2020/10/27
Speech Synthesis  Hmm-based Speech Synthesis  Parametric Representation Of Speech  Excitation Model  Pitch-scaled Spectrum  
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：60/0  |  提交时间：2020/10/27
Analysis-synthesis Framework  Multi-band Summary Correlogram  Denoising Autoencoder  Speech Enhancement  Speech Coding  
Improving Deep Neural Network Based Speech Synthesis through Contextual Feature Parametrization and Multi-Task Learning 期刊论文
JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, 2018, 卷号: 90, 期号: 7, 页码: 1025-1037
作者:  Wen, Zhengqi;  Li, Kehuang;  Huang, Zhen;  Lee, Chin-Hui;  Tao, Jianhua;  Zhengqi Wen
收藏  |  浏览/下载：101/0  |  提交时间：2020/10/27
Dnn-based Speech Synthesis  Vocoder  Speech Parametrization  Blstm  Phoneme Embedded Vector  Multi-task Learning  Pitch-scaled Spectrum  
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：119/0  |  提交时间：2020/10/27
Speech Synthesis  Excitation Parameters  Deep Neural Network Adaptation  Exclamatory Speech  Interrogative Speech  
Progressive Neural Networks based Features Prediction for the Target Cost in Unit-Selection Speech Synthesizer 会议论文
, 北京, 2018-8
作者:  Fu, Ruibo;  Tao, Jianhua;  Wen, Zhengqi
浏览  |  Adobe PDF(1188Kb)  |  收藏  |  浏览/下载：223/66  |  提交时间：2020/06/27
speech synthesis  progressive neural networks  unit-selection  target cost  
Transfer Learning based Progressive Neural Networks for Acoustic Modeling in Statistical Parametric Speech Synthesis 会议论文
, 印度海得拉巴, 2018-9
作者:  Fu, Ruibo;  Tao, Jianhua;  Zheng, Yibin;  Wen, Zhengqi
浏览  |  Adobe PDF(340Kb)  |  收藏  |  浏览/下载：258/52  |  提交时间：2020/06/27
Deep Metric Learning for the Target Cost in Unit-Selection Speech Synthesizer 会议论文
, 印度海得拉巴, 2018-9
作者:  Fu, Ruibo;  Tao, Jianhua;  Zheng, Yibin;  Wen, Zhengqi
浏览  |  Adobe PDF(323Kb)  |  收藏  |  浏览/下载：280/62  |  提交时间：2020/06/27
speech synthesis  unit-selection  target cost  deep metric learning