Emotion Recognition using Speech Features
“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.
Discusses complete state-of -art features, models and databases in the context of emotion recognition Explores implicit and explicit excitation source features for discriminating the emotions Proposes pitch synchronous and sub-syllabic spectral features, in addition to conventional spectral features, for characterizing emotions