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Emotion Recognition using Speech Features [electronic resource] / by K. Sreenivasa Rao, Shashidhar G. Koolagudi.

Por: Colaborador(es): Tipo de material: TextoTextoSeries SpringerBriefs in Electrical and Computer Engineering, SpringerBriefs in Speech Technology | SpringerBriefs in Electrical and Computer Engineering, SpringerBriefs in Speech TechnologyEditor: New York, NY : Springer New York : Imprint: Springer, 2013Descripción: XII, 124 p. 30 illus., 6 illus. in color. online resourceTipo de contenido:
  • text
Tipo de medio:
  • computer
Tipo de soporte:
  • online resource
ISBN:
  • 9781461451433
Trabajos contenidos:
  • SpringerLink (Online service)
Tema(s): Formatos físicos adicionales: Sin títuloClasificación CDD:
  • 621.382 23
Clasificación LoC:
  • TK5102.9
  • TA1637-1638
  • TK7882.S65
Recursos en línea:
Contenidos:
Springer eBooksResumen: ǣEmotion Recognition Using Speech Featuresǥ covers emotion-specific features present in speech anddiscussion ofsuitable 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. Discussionincludesglobal 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.
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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).

ǣEmotion Recognition Using Speech Featuresǥ covers emotion-specific features present in speech anddiscussion ofsuitable 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. Discussionincludesglobal 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.

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