CASIA OpenIR

浏览/检索结果: 共9条,第1-9条 帮助

限定条件    
已选(0)清除 条数/页:   排序方式:
Tucker decomposition-based temporal knowledge graph completion 期刊论文
KNOWLEDGE-BASED SYSTEMS, 2022, 卷号: 238, 页码: 9
作者:  Shao, Pengpeng;  Zhang, Dawei;  Yang, Guohua;  Tao, Jianhua;  Che, Feihu;  Liu, Tong
Adobe PDF(611Kb)  |  收藏  |  浏览/下载:228/38  |  提交时间:2022/06/10
Temporal knowledge graphs  Tucker decomposition  Reconstruction  Contrastive learning  
Self-supervised graph representation learning via bootstrapping 期刊论文
NEUROCOMPUTING, 2021, 卷号: 456, 页码: 88-96
作者:  Che, Feihu;  Yang, Guohua;  Zhang, Dawei;  Tao, Jianhua;  Liu, Tong
Adobe PDF(1379Kb)  |  收藏  |  浏览/下载:314/56  |  提交时间:2021/11/03
Graph representation learning  Self-supervised  Bootstrapping  Graph neural network  
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:339/46  |  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  
CTNet: Conversational Transformer Network for Emotion Recognition 期刊论文
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2021, 期号: 29, 页码: 985-1000
作者:  Lian, Zheng;  Liu, Bin;  Tao, Jianhua
Adobe PDF(2230Kb)  |  收藏  |  浏览/下载:310/58  |  提交时间:2021/05/06
Emotion recognition  Context modeling  Feature extraction  Fuses  Speech processing  Data models  Bidirectional control  Context-sensitive modeling  conversational transformer network (CTNet)  conversational emotion recognition  multimodal fusion  speaker-sensitive modeling  
Integrating Knowledge Into End-to-End Speech Recognition From External Text-Only Data 期刊论文
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2021, 卷号: 29, 页码: 1340-1351
作者:  Bai, Ye;  Yi, Jiangyan;  Tao, Jianhua;  Wen, Zhengqi;  Tian, Zhengkun;  Zhang, Shuai
收藏  |  浏览/下载:147/0  |  提交时间:2021/06/07
End-to-End  language modeling  speech recognition  teacher-student learning  transfer learning  
F-0-Noise-Robust Glottal Source and Vocal Tract Analysis Based on ARX-LF Model 期刊论文
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2021, 卷号: 29, 页码: 3375-3383
作者:  Li, Yongwei;  Tao, Jianhua;  Erickson, Donna;  Liu, Bin;  Akagi, Masato
收藏  |  浏览/下载:101/0  |  提交时间:2021/12/28
Speech recognition  Iterative methods  Production  Estimation  Brain modeling  Shape  Low-frequency noise  Glottal source  vocal tract  source-filter model  ARX-LF model  
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:251/55  |  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  
Forward-Backward Decoding Sequence for Regularizing End-to-End TTS 期刊论文
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2019, 卷号: 27, 期号: 12, 页码: 2067-2079
作者:  Zheng, Yibin;  Tao, Jianhua;  Wen, Zhengqi;  Yi, Jiangyan
收藏  |  浏览/下载:305/0  |  提交时间:2020/03/30
Decoding  Training  Speech processing  Linguistics  Acoustics  Speech recognition  Forward-backward  regularization  encoder-decoder with attention  end-to-end  joint-training  TTS  
Language-Adversarial Transfer Learning for Low-Resource Speech Recognition 期刊论文
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2019, 卷号: 27, 期号: 3, 页码: 621-630
作者:  Yi, Jiangyan;  Tao, Jianhua;  Wen, Zhengqi;  Bai, Ye
浏览  |  Adobe PDF(907Kb)  |  收藏  |  浏览/下载:369/83  |  提交时间:2019/07/12
Adversarial training  transfer learning  cross-lingual  low-resource  speech recognition