"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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