SPE-75.6
DETERMINING THE BEST ACOUSTIC FEATURES FOR SMOKER IDENTIFICATION
Zhizhong Ma, Yuanhang Qiu, Feng Hou, Ruili Wang, Massey University, New Zealand; Joanna Ting Wai Chu, Christopher Bullen, University of Auckland, New Zealand
Session:
Speech Analysis
Track:
Speech and Language Processing
Location:
Gather Area B
Presentation Time:
Thu, 12 May, 23:00 - 23:45 China Time (UTC +8)
Thu, 12 May, 15:00 - 15:45 UTC
Thu, 12 May, 15:00 - 15:45 UTC
Session Chair:
Hemant Patil, DA-IICT, Gandhinagar, Gujarat, India
Session SPE-75
SPE-75.1: PITCH ESTIMATION BY MULTIPLE OCTAVE DECODERS
Yael Segal, May Arama-Chayoth, Joseph Keshet, Bar-Ilan University, Israel
SPE-75.2: DEEP LEARNING FOR PROMINENCE DETECTION IN CHILDREN'S READ SPEECH
Mithilesh Vaidya, Kamini Sabu, Preeti Rao, Indian Institute of Technology, Bombay, India
SPE-75.3: TOWARDS A COMMON SPEECH ANALYSIS ENGINE
Hagai Aronowitz, Itai Gat, Edmilson Morais, Weizhong Zhu, Ron Hoory, IBM Research AI, Israel
SPE-75.4: Phone-to-audio alignment without text: A Semi-supervised Approach
Jian Zhu, David Jurgens, University of Michigan, United States of America; Cong Zhang, Radboud University, Netherlands
SPE-75.5: ATTACHMENT RECOGNITION IN SCHOOL-AGE CHILDREN: A MULTIMODAL APPROACH BASED ON LANGUAGE AND PARALANGUAGE ANALYSIS
Huda Alsofyani, Alessandro Vinciarelli, University of Glasgow, United Kingdom of Great Britain and Northern Ireland
SPE-75.6: DETERMINING THE BEST ACOUSTIC FEATURES FOR SMOKER IDENTIFICATION
Zhizhong Ma, Yuanhang Qiu, Feng Hou, Ruili Wang, Massey University, New Zealand; Joanna Ting Wai Chu, Christopher Bullen, University of Auckland, New Zealand