Acoustic Modeling for Emotion Recognition

2015
ISBN: 978-3-319-15529-6
Verlag: Springer Nature Switzerland

Buch, Englisch, 66 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1299 g

Reihe: SpringerBriefs in Speech Technology

This book presents state of art research in speech emotion recognition. Readers are first presented with basic research and applications – gradually more advance information is provided, giving readers comprehensive guidance for classify emotions through speech. Simulated databases are used and results extensively compared, with the features and the algorithms implemented using MATLAB. Various emotion recognition models like Linear Discriminant Analysis (LDA), Regularized Discriminant Analysis (RDA), Support Vector Machines (SVM) and K-Nearest neighbor (KNN) and are explored in detail using prosody and spectral features, and feature fusion techniques.

Zielgruppe

Research

Autoren/Hrsg.

Anne, Koteswara Rao

Vankayalapati, Hima Deepthi

Kuchibhotla, Swarna

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Spracherkennung, Sprachverarbeitung
• Sozialwissenschaften Psychologie Allgemeine Psychologie Kognitionspsychologie Emotion, Motivation, Handlung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion
• Geisteswissenschaften Sprachwissenschaft Computerlinguistik, Korpuslinguistik

Inhaltsverzeichnis

Introduction.- Emotion Recognition using Prosodic features.- Emotion Recognition using Spectral features.- Emotional Speech Corpora.- Classification Models.- Comparative Analysis of Classifiers in emotion recognition.- Summary and Conclusions.