Design of FIS-Based Model for Emotional Speech Recognition

Human beings have emotions associated with their acts and speeches. The emotional expressions vary with moods and situations. Speech is an important medium through which people express their feelings. Prosodic, spectral, and other parameters of speech vary with the emotions. The ability to represent the emotional speech varies with the type of features chosen. In an attempt to recognize such an emotional content of speech, one of the spectral features (linear prediction coefficients), have been first tested by the fuzzy interference system. Next to it hybridization of LPC features with different prosodic features were compared with LPC features for recognition accuracy. Results show that the hybridization of features can classify emotions better with the FIS system.