SPE-41: Voice Activity and Disfluency Detection |
Session Type: Poster |
Time: Thursday, 10 June, 15:30 - 16:15 |
Location: Gather.Town |
Virtual Session: View on Virtual Platform |
Session Chair: Douglas O'Shaughnessy, INSR |
SPE-41.1: SEP-28K: A DATASET FOR STUTTERING EVENT DETECTION FROM PODCASTS WITH PEOPLE WHO STUTTER |
Colin Lea; Apple |
Vikramjit Mitra; Apple |
Aparna Joshi; Apple |
Sachin Kajarekar; Apple |
Jeffrey Bigham; Apple |
SPE-41.2: A HYBRID CNN-BILSTM VOICE ACTIVITY DETECTOR |
Nicholas Wilkinson; Stellenbosch University |
Thomas Niesler; Stellenbosch University |
SPE-41.3: SELF-ATTENTIVE VAD: CONTEXT-AWARE DETECTION OF VOICE FROM NOISE |
Yong Rae Jo; Voithru |
Young Ki Moon; Voithru, Inha University |
Won Ik Cho; Seoul National University |
Geun Sik Jo; Inha University |
SPE-41.4: PREVENTING EARLY ENDPOINTING FOR ONLINE AUTOMATIC SPEECH RECOGNITION |
Yingzhu Zhao; Nanyang Technological University |
Chongjia Ni; Alibaba Group |
Cheung-Chi Leung; Alibaba Group |
Shafiq Joty; Nanyang Technological University |
Eng Siong Chng; Nanyang Technological University |
Bin Ma; Alibaba Group |
SPE-41.5: MARBLENET: DEEP 1D TIME-CHANNEL SEPARABLE CONVOLUTIONAL NEURAL NETWORK FOR VOICE ACTIVITY DETECTION |
Fei Jia; NVIDIA Corporation |
Somshubra Majumdar; NVIDIA Corporation |
Boris Ginsburg; NVIDIA Corporation |
SPE-41.6: SPEECH ENHANCEMENT AIDED END-TO-END MULTI-TASK LEARNING FOR VOICE ACTIVITY DETECTION |
Xu Tan; Northwestern Polytechnical University |
Xiao-Lei Zhang; Northwestern Polytechnical University |
SPE-41.7: ROBUST VOICE ACTIVITY DETECTION USING A MASKED AUDITORY ENCODER BASED CONVOLUTIONAL NEURAL NETWORK |
Nan Li; Tianjin university |
Longbiao Wang; Tianjin university |
Masashi Unoki; Japan Advanced Institute of Science and Technology |
Sheng Li; National Institute of Information and Communications Technology |
Rui Wang; Japan Advanced Institute of Science and Technology |
Meng Ge; Tianjin university |
Jianwu Dang; Japan Advanced Institute of Science and Technology and Tianjin University |