Emotion recognition is the gap in today’s Human Computer Interaction (HCI). These systems lack the ability to effectively recognize, express and feel emotion limits in their human interaction. They still lack the better sensitivity to human emotions. Multi modal emotion recognition attempts to addresses this gap by measuring emotional state from gestures, facial expressions, acoustic characteristics, textual expressions. Multi modal data acquired from video, audio, sensors etc. are combined using various techniques to classify basis human emotions like happiness, joy, neutrality, surprise, sadness, disgust, fear, anger etc. This work presents a critical analysis of multi modal emotion recognition approaches in meeting the requirements of next generation human computer interactions. The study first explores and defines the requirements of next generation human computer interactions and critically analyzes the existing multi modal emotion recognition approaches in addressing those requirements
