Acoustic Modeling for Emotion Recognition

Beschreibung

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.

Provides comprehensive research and application on classification of emotions through speech Features extensive comparative study of classifiers, presenting results in different databases Compares feature fusion techniques with emotions of individual features Includes supplementary material: sn.pub/extras

Autor*in

Koteswara Rao Anne

Themen in »Acoustic Modeling for Emotion Recognition«

Classifying Emotions in Speech Emotion Recognition in Speech Feature Fusion Techniques K-Nearest neighbor Linear Discriminant Analysis Receiver Operating Characteristic Regularized Discriminant Analysis Speech Signal Processing Support Vector Machines

Stimmen zu »Acoustic Modeling for Emotion Recognition«

“The aim of this book is to bring out various features through speech processing, and use them in an acoustic model to recognize the emotion conveyed by the person. … the monogram looks concise and interesting and should be of interest to postgraduates and researchers in speech processing.” (Soubhik Chakraborty, Computing Reviews, April, 2016)

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