Pathological Voice Analysis

David Zhang graduated in Computer Science from Peking University. He received his MSc and PhD in Computer Science from the Harbin Institute of Technology (HIT), in 1982 and 1985 respectively. From 1986 to 1988 he was a Postdoctoral Fellow at Tsinghua University and then an Associate Professor at the Academia Sinica, Beijing. In 1994 he received his second PhD in Electrical and Computer Engineering from the University of Waterloo, Ontario, Canada. Currently, he is with the School of Science and Engineering, The Chinese University of Hong Kong (Shenzhen), China. He also serves as Visiting Chair Professor at Tsinghua University and HIT, and Adjunct Professor at Jiao Tong University, Peking University, the National University of Defense Technology and the University of Waterloo. He is the founder and editor-in-chief of the International Journal of Image and Graphics (IJIG); book editor for the Springer International Series on Biometrics (KISB); organizer of the first International Conference on Biometrics Authentication (ICBA); and associate editor of more than ten international journals, including IEEE Transactions. He has published over 20 monographs, 400 international journal papers and 40 patents in the USA/Japan/HK/China. He was listed as a Highly Cited Researcher in Engineering by Clarivate Analytics (formerly known as Thomson Reuters) in 2014, 2015, 2016, 2017 and 2018. Professor Zhang is a Croucher Senior Research Fellow, Distinguished Speaker of the IEEE Computer Society, and a Fellow of both IEEE and IAPR. Kebin Wu received her B.S. degree in Electronic and Information Engineering from the Harbin Institute of Technology in 2011 and her Ph.D. degree from Tsinghua University in 2018. Her research interests include pathological voice analysis, computer vision and statistical pattern recognition.

PART I: OVERVIEW
Chapter 1 INTRODUCTION 1.1Voice Analysis1.2Traditional Applications1.3A New Trend: Biomedical Application 1.4SummaryREFERENCES
Chapter 2 VOICE ACQUISITION2.1Introduction2.2Voice Collection System2.3Optimization of Sampling Rate2.4SummaryREFERENCES
PART II: PREPROCESSING OF VOICE SIGNAL
Chapter 3 PITCH ESTIMATION3.1Introduction3.2iPEEH: Improving Pitch Estimation by Enhancing Harmonics 3.3Experimental Results and Analysis3.4SummaryREFERENCES
Chapter 4 GLOTTAL CLOSURE INSTANTS (GCI) DETECTION4.1Introduction4.2Background of TKEO And Its Relationship With GCI 4.3GMAT: Glottal Closure Instants Detection Based on The Multiresolution Absolute Teager-Kaiser Energy Operator 4.4Experimental Results and Discussion4.5SummaryREFERENCES

PART III: FEATURE EXTRACTION AND LEARNING
Chapter 5 FEATURE EXTRACTION5.1Introduction5.2Basic Feature5.3High-Order Feature5.4Stability Feature5.5SummaryREFERENCES
Chapter 6 FEATURE LEARNING6.1Introduction6.2Feature Learning Based on Spherical Kmeans6.3Experiments and Analysis6.4SummaryREFERENCES
PART IV: MULTI-AUDIO FUSION
Chapter 7 JOINT LEARNING FOR VOICE BASED DISEASE DETECTION7.1Introduction7.2Fusion Based on Label Relaxed Low-Rank Ridge Regression 7.3Performance Evaluation7.4Discussion7.5SummaryREFERENCES
Chapter 8 ROBUST MULTI-VIEW DISCRIMINATIVE LEARNING8.1Introduction8.2Fusion Based On Shared-Specific Structures 8.3Experimental Results and Performance Evaluation8.4Discussion8.5SummaryREFERENCES
PART V: APPLICATION SYSTEM
Chapter 9 A VOICE ANALYSIS SYSTEM 9.1Introduction9.2A Voice Analysis System for Pathology Detection9.3Discussion9.4SummaryREFERENCES
Chapter 10 BOOK REVIEW AND FUTURE WORK10.1Book Recapitulation10.2Future Work