Emotion Recognition using Speech Features

Nonfiction, Computers, Advanced Computing, Programming, User Interfaces, Science & Nature, Technology, Electronics
Cover of the book Emotion Recognition using Speech Features by K. Sreenivasa Rao, Shashidhar G. Koolagudi, Springer New York
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Author: K. Sreenivasa Rao, Shashidhar G. Koolagudi ISBN: 9781461451433
Publisher: Springer New York Publication: November 7, 2012
Imprint: Springer Language: English
Author: K. Sreenivasa Rao, Shashidhar G. Koolagudi
ISBN: 9781461451433
Publisher: Springer New York
Publication: November 7, 2012
Imprint: Springer
Language: English

“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.

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“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.

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