Normal View MARC View ISBD View

Emotion Recognition using Speech Features

by Rao, K. Sreenivasa.
Authors: Koolagudi, Shashidhar G.%author. | SpringerLink (Online service) Series: SpringerBriefs in Electrical and Computer Engineering, SpringerBriefs in Speech Technology, 2191-8112 Physical details: XII, 124 p. 30 illus., 6 illus. in color. online resource. ISBN: 1461451434 Subject(s): Engineering. | Computer science. | Computational linguistics. | Engineering. | Signal, Image and Speech Processing. | User Interfaces and Human Computer Interaction. | Computational Linguistics.
Tags from this library:
No tags from this library for this title.
Item type Location Call Number Status Date Due
E-Book E-Book AUM Main Library 621.382 (Browse Shelf) Not for loan

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).

“Emotion Recognition Using Speech Features” covers emotion-specific features present in speech and discussion of 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. 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 using evidence derived from various features and models. The acquired emotion-specific knowledge is useful for synthesizing emotions. Discussion includes global and local prosodic features at syllable, word and phrase levels, helpful for capturing emotion-discriminative information; use of complementary evidences obtained from excitation sources, vocal tract systems and prosodic features in order to enhance the emotion recognition performance;  and proposed multi-stage and hybrid models for improving the emotion recognition performance.

There are no comments for this item.

Log in to your account to post a comment.