The emotion of a human could be identified using Speech, Image and Question and answer session. Also, the emotion in speech is identified using the pitch and intensity. The emotion identification with image is done using Support Vector Machine. The present chapter envisages into an intelligent system, which is designed to understand human emotions more precisely speech emotion identification and intends to generate actions via cognitive system. It has mainly focused on developing an online incremental learning system of human emotions using Takagi-Sugeno (TS) Fuzzy model. The main objective of this system is to detect whether the observed emotion needs a new corresponding multi-model action to be generated or it can be attributed to one of the existing actions in memory. The multi-model consists of voice input, facial expression. The combined results have been classified using TS Fuzzy Model.

Keywords: Mel Frequency Cepstral Coefficient, Speech, Emotion, Identification, TS Fuzzy Model, Pitch, Intensity, Cognitive, Image