Description
“Emotion Recognition Using Speech Features” provides coverage of emotion-specific features present in speech. The author also discusses suitable models for capturing emotion-specific information for distinguishing different emotions. The content of this book is important for designing and developing natural and sophisticated speech systems.In this Brief, Drs. Rao and Koolagudi lead a discussion of how emotion-specific information is embedded in speech and how to acquire emotion-specific knowledge using appropriate statistical models. Additionally, the authors provide information about exploiting multiple evidences derived from various features and models. The acquired emotion-specific knowledge is useful for synthesizing emotions. Features includes discussion of:• Global and local prosodic features at syllable, word and phrase levels, helpful for capturing emotion-discriminative information;• Exploiting complementary evidences obtained from excitation sources, vocal tract systems and prosodic features in order to enhance the emotion recognition performance;• Proposed multi-stage and hybrid models for improving the emotion recognition performance.This brief is for researchers working in areas related to speech-based products such as mobile phone manufacturing companies, automobile companies, and entertainment products as well as researchers involved in basic and applied speech processing research.
Table of Contents
Introduction.- Speech Emotion Recognition: A Review.- Emotion Recognition Using Excitation Source Information.- Emotion Recognition Using Vocal Tract Information.- Emotion Recognition Using Prosodic Information.- Summary and Conclusions.- Linear Prediction Analysis of Speech.- MFCC Features.- Gaussian Mixture Model (GMM)
