"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.