Technical Program

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SPE-P2: Speech Enhancement I: Network Architectures

Session Type: Poster
Time: Tuesday, 5 May, 11:30 - 13:30
Location: On-Demand
Virtual Session: View on Virtual Platform
Session Chairs: Afsaneh Asaei, UnternehmerTUM and Timo Gerkmann, Universität Hamburg
 
 SPE-P2.1: CP-GAN: CONTEXT PYRAMID GENERATIVE ADVERSARIAL NETWORK FOR SPEECH ENHANCEMENT
         Gang Liu; Sun Yat-Sen University
         Ke Gong; DarkMatter AI Research
         Xiaodan Liang; Sun Yat-Sen University
         Zhiguang Chen; Sun Yat-Sen University
 
 SPE-P2.2: DENSELY CONNECTED NEURAL NETWORK WITH DILATED CONVOLUTIONS FOR REAL-TIME SPEECH ENHANCEMENT IN THE TIME DOMAIN
         Ashutosh Pandey; Ohio State University
         DeLiang Wang; Ohio State University
 
 SPE-P2.3: PAN: PHONEME-AWARE NETWORK FOR MONAURAL SPEECH ENHANCEMENT
         Zhihao Du; Harbin Institute of Technology
         Ming Lei; Alibaba Group
         Jiqing Han; Harbin Institute of Technology
         Shiliang Zhang; Alibaba Group
 
 SPE-P2.4: EFFICIENT TRAINABLE FRONT-ENDS FOR NEURAL SPEECH ENHANCEMENT
         Jonah Casebeer; University of Illinois at Urbana–Champaign
         Umut Isik; Amazon Web Services
         Shrikant Venkataramani; University of Illinois at Urbana–Champaign
         Arvindh Krishnaswamy; Amazon Web Services
 
 SPE-P2.5: INVERTIBLE DNN-BASED NONLINEAR TIME-FREQUENCY TRANSFORM FOR SPEECH ENHANCEMENT
         Daiki Takeuchi; Waseda University
         Kohei Yatabe; Waseda University
         Yuma Koizumi; NTT Corporation
         Yasuhiro Oikawa; Waseda University
         Noboru Harada; NTT Corporation
 
 SPE-P2.6: T-GSA: TRANSFORMER WITH GAUSSIAN-WEIGHTED SELF-ATTENTION FOR SPEECH ENHANCEMENT
         Jaeyoung Kim; Google
         Mostafa El-Khamy; Samsung Semiconductor, Inc.
         Jungwon Lee; Samsung Semiconductor, Inc.
 
 SPE-P2.7: REDUNDANT CONVOLUTIONAL NETWORK WITH ATTENTION MECHANISM FOR MONAURAL SPEECH ENHANCEMENT
         Tian Lan; University of Electronic Science and Technology of China
         Yilan Lyu; University of Electronic Science and Technology of China
         Guoqiang Hui; University of Electronic Science and Technology of China
         Refuoe Mokhosi; University of Electronic Science and Technology of China
         Sen Li; University of Electronic Science and Technology of China
         Qiao Liu; University of Electronic Science and Technology of China
 
 SPE-P2.8: RESIDUAL RECURRENT NEURAL NETWORK FOR SPEECH ENHANCEMENT
         Jalal Abdulbaqi; Rutgers, The State University of New Jersey
         Yue Gu; Rutgers, The State University of New Jersey
         Shuhong Chen; Rutgers, The State University of New Jersey
         Ivan Marsic; Rutgers, The State University of New Jersey
 
 SPE-P2.9: 2D-TO-2D MASK ESTIMATION FOR SPEECH ENHANCEMENT BASED ON FULLY CONVOLUTIONAL NEURAL NETWORK
         Yanhui Tu; University of Science and Technology of China
         Jun Du; University of Science and Technology of China
         Chin-Hui Lee; Georgia Institute of Technology
 
 SPE-P2.10: SELF-SUPERVISED DENOISING AUTOENCODER WITH LINEAR REGRESSION DECODER FOR SPEECH ENHANCEMENT
         Ryandhimas Edo Zezario; Academia Sinica
         Tassadaq Hussain; Academia Sinica
         Xugang Lu; National Institute of Information and Communications Technology (NICT)
         Hsin-Min Wang; Academia Sinica
         Yu Tsao; Academia Sinica
 
 SPE-P2.11: FULLY CONVOLUTIONAL RECURRENT NETWORKS FOR SPEECH ENHANCEMENT
         Maximilian Strake; Technische Universität Braunschweig
         Bruno Defraene; NXP Semiconductors
         Kristoff Fluyt; NXP Semiconductors
         Wouter Tirry; NXP Semiconductors
         Tim Fingscheidt; Technische Universität Braunschweig
 
 SPE-P2.12: PHONETIC FEEDBACK FOR SPEECH ENHANCEMENT WITH AND WITHOUT PARALLEL SPEECH DATA
         Peter Plantinga; Ohio State University
         Deblin Bagchi; Ohio State University
         Eric Fosler-Lussier; Ohio State University