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 |
|