Recognising Emotions from Keyboard Stroke Pattern

In day to day life, emotions are becoming an important tool which helps to take not only the decisions but also to enhance learning, creative thinking and to effectively correspond in the social interaction. Several studies have been conducted comprising of classical human human interaction and human computer interaction. They concluded that for intelligent interaction, emotions play an important role. By embedding the emotions in the interaction of human with machine, machine would be in a position to sense the mood of the user and change its interaction accordingly. Hence the system will be friendlier to the user and its responses will be more similar to human behaviour. In general, human beings make use of emotions through speech, facial expression and gestures for conveying the crucial information. This paper presents an attempt to recognize selected emotion categories from keyboard stroke pattern. The emotional categories considered for our analysis are neutral, positive and negative. We have used various classifiers like Simple Logistics, SMO, Multilayer Perceptron, Random Tree, J48 and BF Tree, which is a part of WEKA tool, to analyse the selected features from keyboard stroke pattern.