云南高校图书馆联盟文献共享服务平台- SPEECH

SPEECH_ENHANCEMENT: 作品数：63被引量：92H指数：4; 导出分析报告; 相关作者：赵力陈国明邹采荣石鸿凌刘卓夫更多>>; 相关机构：东南大学重庆邮电大学武汉大学中国地震局工程力学研究所更多>>; 相关期刊：更多>>; 相关基金：国家自然科学基金国家高技术研究发展计划国家重点基础研究发展计划北京市自然科学基金更多>>

Teacher-Student Training Approach Using an Adaptive Gain Mask for LSTM-Based Speech Enhancement in the Airborne Noise Environment: 《Chinese Journal of Electronics》2023年第4期882-895,共14页HUANG Ping WU Yafeng; This work was supported by the Fundamental Research Funds for the Central Universities(D5000210974).; Research on speech enhancement algorithms in the airborne environment is of great significance to the security of airborne systems.Recently,the research focus of speech enhancement has turned from conventional unsuper...; 关键词：Adaptive ideal mask Teacher-student learning Long short-term memory(LSTM) Speech enhancement

Mobile Communication Voice Enhancement Under Convolutional Neural Networks and the Internet of Things: 《Intelligent Automation & Soft Computing》2023年第7期777-797,共21页Jiajia Yu; supported by General Project of Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province(2022SJYB0712);Research Development Fund for Young Teachers of Chengxian College of Southeast University(z0037);Special Project of Ideological and Political Education Reform and Research Course(yjgsz2206).; This study aims to reduce the interference of ambient noise in mobile communication,improve the accuracy and authenticity of information transmitted by sound,and guarantee the accuracy of voice information deliv-ered ...; 关键词：Convolutional neural networks speech enhancement noise recognition deep learning human-computer interaction Internet of Things

Adversarial Examples Protect Your Privacy on Speech Enhancement System: 《Computer Systems Science & Engineering》2023年第7期1-12,共12页Mingyu Dong Diqun Yan Rangding Wang; This work was supported by the National Natural Science Foundation of China(Grant No.61300055);Zhejiang Natural Science Foundation(Grant No.LY20F020010);Ningbo Science and Technology Innovation Project(Grant No.2022Z075);Ningbo Natural Science Foundation(Grant No.202003N4089);K.C.Wong Magna Fund in Ningbo University.; Speech is easily leaked imperceptibly.When people use their phones,the personal voice assistant is constantly listening and waiting to be activated.Private content in speech may be maliciously extracted through automa...; 关键词：Adversarial example speech enhancement privacy protection deep neural network

Using Hybrid Penalty and Gated Linear Units to Improve Wasserstein Generative Adversarial Networks for Single-Channel Speech Enhancement: 《Computer Modeling in Engineering & Sciences》2023年第6期2155-2172,共18页Xiaojun Zhu Heming Huang; supported by the National Science Foundation under Grant No.62066039.; Recently,speech enhancement methods based on Generative Adversarial Networks have achieved good performance in time-domain noisy signals.However,the training of Generative Adversarial Networks has such problems as con...; 关键词：Speech enhancement generative adversarial networks hybrid penalty gated linear units multi-scale convolution

Improving Speech Enhancement Framework via Deep Learning: 《Computers, Materials & Continua》2023年第5期3817-3832,共16页Sung-Jung Hsiao Wen-Tsai Sung; This research was supported by the Department of Electrical Engineering at National Chin-Yi University of Technology.The authors would like to thank the National Chin-Yi University of Technology,TakmingUniversity of Science and Technology,Taiwan,for supporting this research.; Speech plays an extremely important role in social activities.Many individuals suffer from a“speech barrier,”which limits their communication with others.In this study,an improved speech recognitionmethod is propose...; 关键词：Artificial intelligence speech recognition speech to text CTC-CNN

Monaural speech enhancement using U-net fused with multi-head self-attention: 《Chinese Journal of Acoustics》2023年第1期98-118,共21页FAN Junyi YANG Jibin ZHANG Xiongwei ZHENG Changyan; supported by the National Natural Science Foundation of China(62071484)。; Under low signal-to-noise ratio(SNR)and burst noise conditions,the speech enhancement effect of existing deep learning network models is not satisfactory.In contrast,humans can exploit the long-term correlation of spe...; 关键词：network SPEECH noise

Real-Time Speech Enhancement Based on Convolutional Recurrent Neural Network: 《Intelligent Automation & Soft Computing》2023年第2期1987-2001,共15页S.Girirajan A.Pandian; Speech enhancement is the task of taking a noisy speech input and pro-ducing an enhanced speech output.In recent years,the need for speech enhance-ment has been increased due to challenges that occurred in various app...; 关键词：Speech enhancement convolutional encoder-decoder long short-term memory noise suppression speech restoration

Speech Enhancement via Mask-Mapping Based Residual Dense Network: 《Computers, Materials & Continua》2023年第1期1259-1277,共19页Lin Zhou Xijin Chen Chaoyan Wu Qiuyue Zhong Xu Cheng Yibin Tang; supported by the National Key Research and Development Program of China under Grant 2020YFC2004003 and Grant 2020YFC2004002;the National Nature Science Foundation of China(NSFC)under Grant No.61571106.; Masking-based and spectrum mapping-based methods are the two main algorithms of speech enhancement with deep neural network(DNN).But the mapping-based methods only utilizes the phase of noisy speech,which limits the u...; 关键词：Mask-mapping-based method residual dense block speech enhancement

Application of improved U-Net network with attention mechanism in end-to-end speech enhancement: 《Chinese Journal of Acoustics》2022年第4期390-403,共14页WU Ruiqin CHEN Xueqin YU Jie WANG Lirong ZHAO Heming; supported by the National Natural Science Foundation of China(61340004)。; An improved U-Net(Attention Dilated Convolution U-Net,ADC-U-Net)network model for end-to-end speech enhancement is designed based on the U-Net network.Compared with the baseline U-Net network,the dilated convolution i...; 关键词：NETWORK SPEECH MECHANISM

Optimizing the Perceptual Quality of Time-Domain Speech Enhancement with Reinforcement Learning被引量：1: 《Tsinghua Science and Technology》2022年第6期939-947,共9页Xiang Hao Chenglin Xu Lei Xie Haizhou Li; supported by the National Research Foundation of Singapore(No.AISG-100E-2018-006);Human-Robot Interaction Phase 1(No.1922500054);under the National Robotics Programme,Singapore.; In neural speech enhancement,a mismatch exists between the training objective,i.e.,Mean-Square Error(MSE),and perceptual quality evaluation metrics,i.e.,perceptual evaluation of speech quality and short-time objective...; 关键词：speech enhancement neural networks dynamic filter reinforcement learning

SPEECH_ENHANCEMENT