Pathological Voice Analysis / by David Zhang, Kebin Wu

Von:

Zhang, David [VerfasserIn]

Mitwirkende(r):

Wu, Kebin [VerfasserIn]

Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: Springer eBook CollectionVerlag: Singapore : Springer Singapore, 2020Verlag: Singapore : Imprint: Springer, 2020Auflage: 1st ed. 2020Beschreibung: 1 Online-Ressource(X, 174 p. 44 illus., 41 illus. in color.)ISBN:

9789813291966

Schlagwörter:

Andere physische Formen: 9789813291959 | 9789813291973 | 9789813291980 | Erscheint auch als: 9789813291959 Druck-Ausgabe | Erscheint auch als: 9789813291973 Druck-Ausgabe | Erscheint auch als: 9789813291980 Druck-AusgabeDOI: DOI: 10.1007/978-981-32-9196-6Online-Ressourcen:

Zusammenfassung: CHAPTER 1 INTRODUCTION -- CHAPTER 2 PATHOLOGICAL VOICE ACQUISITION -- CHAPTER 3 PITCH ESTIMATION -- CHAPTER 4 GLOTTAL CLOSURE INSTANTS DETECTION -- CHAPTER 5 FEATURE LEARNING -- CHAPTER 6 JOINT LEARNING FOR VOICE BASED DISEASE DETECTION -- CHAPTER 7 ROBUST MULTI VIEW DISCRIMINATIVE LEARNING FOR VOICE BASED DISEASE DETECTION -- CHAPTER 8 BOOK REVIEW AND FUTURE WORK.Zusammenfassung: 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. .PPN: PPN: 1728474787Package identifier: Produktsigel: ZDB-2-SCS | ZDB-2-SEB | ZDB-2-SXCS

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