1.

Record Nr.

UNISA996465468603316

Autore

Zhang David

Titolo

Pathological Voice Analysis [[electronic resource] /] / by David Zhang, Kebin Wu

Pubbl/distr/stampa

Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020

ISBN

981-329-196-6

Edizione

[1st ed. 2020.]

Descrizione fisica

1 online resource (X, 174 p. 44 illus., 41 illus. in color.)

Disciplina

616.85

Soggetti

Pattern recognition

Signal processing

Image processing

Speech processing systems

Biomedical engineering

Speech pathology

Pattern Recognition

Signal, Image and Speech Processing

Biomedical Engineering and Bioengineering

Speech Pathology

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Includes index.

Nota di contenuto

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.

Sommario/riassunto

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. .