AUD-18.4
SUPERVISED AND SELF-SUPERVISED PRETRAINING BASED COVID-19 DETECTION USING ACOUSTIC BREATHING/COUGH/SPEECH SIGNALS
Xing-Yu Chen, Qiu-Shi Zhu, Jie Zhang, Li-Rong Dai, University of Science and Technology of China, China
Session:
Medical Acoustics
Track:
Audio and Acoustic Signal Processing
Location:
Gather Area K
Presentation Time:
Tue, 10 May, 23:00 - 23:45 China Time (UTC +8)
Tue, 10 May, 15:00 - 15:45 UTC
Tue, 10 May, 15:00 - 15:45 UTC
Session Chair:
Justin Salamon, Adobe, Inc
Session AUD-18
AUD-18.1: CSENET: COMPLEX SQUEEZE-AND-EXCITATION NETWORK FOR SPEECH DEPRESSION LEVEL PREDICTION
Cunhang Fan, Zhao Lv, Shengbing Pei, Anhui Province Key Laboratory of Multimodal Cognitive Computation, School of Computer Science and Technology, Anhui University, Hefei 230601, China, China; Mingyue Niu, School of Computer and Information Engineering, Tianjin Normal University, Tianjin 300387, China, China
AUD-18.2: UBILUNG: MULTI-MODAL PASSIVE-BASED LUNG HEALTH ASSESSMENT
Ebrahim Nemati, Viswam Nathan, Korosh Vatanparvar, Tousif Ahmed, Md. Mahbubur Rahman, Dan McCaffrey, Jilong Kuang, Alex Gao, Samsung Research America, United States of America; Xuhai Xu, University of Washington, United States of America
AUD-18.3: The Second DiCOVA Challenge: Dataset and performance analysis for Diagnosis of COVID-19 using acoustics
Neeraj Kumar Sharma, Srikanth Raj Chetupalli, Debarpan Bhattacharya, Debottam Dutta, Pravin Mote, Sriram Ganapathy, Indian Institute of Science, India
AUD-18.4: SUPERVISED AND SELF-SUPERVISED PRETRAINING BASED COVID-19 DETECTION USING ACOUSTIC BREATHING/COUGH/SPEECH SIGNALS
Xing-Yu Chen, Qiu-Shi Zhu, Jie Zhang, Li-Rong Dai, University of Science and Technology of China, China
AUD-18.5: EXPLORING AUDITORY ACOUSTIC FEATURES FOR THE DIAGNOSIS OF COVID-19
Madhu Kamble, Jose Patino, Maria A. Zuluaga, Massimiliano Todisco, EURECOM, France, France