Library of American University of Madaba
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Rao, K. Sreenivasa.
Emotion Recognition using Speech Features [electronic resource] / by K. Sreenivasa Rao, Shashidhar G. Koolagudi. - XII, 124 p. 30 illus., 6 illus. in color. online resource. - SpringerBriefs in Electrical and Computer Engineering, SpringerBriefs in Speech Technology, 2191-8112 .
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.
9781461451433
Engineering.
Computer science.
Computational linguistics.
Engineering.
Signal, Image and Speech Processing.
User Interfaces and Human Computer Interaction.
Computational Linguistics.
621.382
Emotion Recognition using Speech Features [electronic resource] / by K. Sreenivasa Rao, Shashidhar G. Koolagudi. - XII, 124 p. 30 illus., 6 illus. in color. online resource. - SpringerBriefs in Electrical and Computer Engineering, SpringerBriefs in Speech Technology, 2191-8112 .
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.
9781461451433
Engineering.
Computer science.
Computational linguistics.
Engineering.
Signal, Image and Speech Processing.
User Interfaces and Human Computer Interaction.
Computational Linguistics.
621.382