Pathological Voice Analysis (eBook)
X, 174 Seiten
Springer Singapore (Verlag)
978-981-329-196-6 (ISBN)
While voice is widely used in speech recognition and speaker identification, its application in biomedical fields is much less common. This book systematically introduces the authors' research on voice analysis for biomedical applications, particularly pathological voice analysis.
Firstly, it reviews the field to highlight the biomedical value of voice. It then offers a comprehensive overview of the workflow and aspects of pathological voice analysis, including voice acquisition systems, voice pitch estimation methods, glottal closure instant detection, feature extraction and learning, and the multi-audio fusion approaches. Lastly, it discusses the experimental results that have shown the superiority of these techniques.
This book is useful to researchers, professionals and postgraduate students working in fields such as speech signal processing, pattern recognition, and biomedical engineering. It is also a valuable resource for those involved in interdisciplinary research.
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.
While voice is widely used in speech recognition and speaker identification, its application in biomedical fields is much less common. This book systematically introduces the authors' research on voice analysis for biomedical applications, particularly pathological voice analysis. Firstly, it reviews the field to highlight the biomedical value of voice. It then offers a comprehensive overview of the workflow and aspects of pathological voice analysis, including voice acquisition systems, voice pitch estimation methods, glottal closure instant detection, feature extraction and learning, and the multi-audio fusion approaches. Lastly, it discusses the experimental results that have shown the superiority of these techniques. This book is useful to researchers, professionals and postgraduate students working in fields such as speech signal processing, pattern recognition, and biomedical engineering. It is also a valuable resource for those involved in interdisciplinary research.
Erscheint lt. Verlag | 3.8.2020 |
---|---|
Zusatzinfo | X, 174 p. 44 illus., 41 illus. in color. |
Sprache | englisch |
Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
Medizin / Pharmazie ► Gesundheitsfachberufe ► Logopädie | |
Medizin / Pharmazie ► Physiotherapie / Ergotherapie ► Orthopädie | |
Technik ► Elektrotechnik / Energietechnik | |
Technik ► Medizintechnik | |
Schlagworte | Biomedical application of voice • feature extraction • Feature learning • Glottal closure instant estimation • Harmonic enhancement • Multi-audio fusion • Multi-audio learning • pattern recognition • Voice analysis • Voice collection system |
ISBN-10 | 981-329-196-6 / 9813291966 |
ISBN-13 | 978-981-329-196-6 / 9789813291966 |
Haben Sie eine Frage zum Produkt? |
Größe: 4,8 MB
DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasserzeichen und ist damit für Sie personalisiert. Bei einer missbräuchlichen Weitergabe des eBooks an Dritte ist eine Rückverfolgung an die Quelle möglich.
Dateiformat: PDF (Portable Document Format)
Mit einem festen Seitenlayout eignet sich die PDF besonders für Fachbücher mit Spalten, Tabellen und Abbildungen. Eine PDF kann auf fast allen Geräten angezeigt werden, ist aber für kleine Displays (Smartphone, eReader) nur eingeschränkt geeignet.
Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.
Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.
aus dem Bereich