GC-P13: Universality, Robustness, and Generalizability for EnhancemeNT (URGENT)
Poster
Fri, 8 May, 14:00 - 16:00
Location: Poster Area 43
Session Type: Poster
Track: SP Grand Challenges
Click the to view the manuscript on IEEE Xplore Open Preview

GC-P13.1: GAP-URGENET: A GENERATIVE-PREDICTIVE FUSION FRAMEWORK FOR UNIVERSAL SPEECH ENHANCEMENT
Xiaobin Rong, Yushi Wang, Zheng Wang, Jing Lu, Nanjing University, China

GC-P13.2: THREE-STAGE BSRNN FOR UNIVERSAL SPEECH ENHANCEMENT AND DATA CURATION USING A LARGE PRE-TRAINED SPEECH RESTORATION MODEL
Ryutaro Matsunaga, Ryo Takahashi, SoftBank Corp., Japan; Shinnosuke Takamichi, Keio University, Japan

GC-P13.3: A HYBRID DISCRIMINATIVE AND GENERATIVE SYSTEM FOR UNIVERSAL SPEECH ENHANCEMENT
Yinghao Liu, Chengwei Liu, Xiaotao Liang, Haoyin Yan, Shaofei Xue, Zheng Xue, Alibaba Group, China

GC-P13.4: HYBRID SPEECH ENHANCEMENT WITH DISCRIMINATIVE AND CODEC TOKEN PREDICTION MODELS GUIDED BY CLEANED SSL FEATURES FOR THE ICASSP 2026 URGENT CHALLENGE
Nabarun Goswami, Tatsuya Harada, The University of Tokyo, Japan

GC-P13.5: ICASSP 2026 URGENT Speech Enhancement Challenge
Chenda Li, Wei Wang, Shanghai Jiao Tong University, China; Marvin Sach, Universität Braunschweig, Germany; Wangyou Zhang, Shanghai Jiao Tong University, China; Kohei Saijo, Waseda University, Japan; Samuele Cornell, Carnegie Mellon University, United States of America; Yihui Fu, Universität Braunschweig, Germany; Zhaoheng Ni, Meta, United States of America; Tim Fingscheidt, Universität Braunschweig, Germany; Shinji Watanabe, Carnegie Mellon University, United States of America; Yanmin Qian, Shanghai Jiao Tong University, China