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Recognising Emotions from Keyboard Stroke Pattern

by Preeti Khanna, M.Sasikumar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 11 - Number 9
Year of Publication: 2010
Authors: Preeti Khanna, M.Sasikumar
10.5120/1614-2170

Preeti Khanna, M.Sasikumar . Recognising Emotions from Keyboard Stroke Pattern. International Journal of Computer Applications. 11, 9 ( December 2010), 1-5. DOI=10.5120/1614-2170

@article{ 10.5120/1614-2170,
author = { Preeti Khanna, M.Sasikumar },
title = { Recognising Emotions from Keyboard Stroke Pattern },
journal = { International Journal of Computer Applications },
issue_date = { December 2010 },
volume = { 11 },
number = { 9 },
month = { December },
year = { 2010 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume11/number9/1614-2170/ },
doi = { 10.5120/1614-2170 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:00:05.569020+05:30
%A Preeti Khanna
%A M.Sasikumar
%T Recognising Emotions from Keyboard Stroke Pattern
%J International Journal of Computer Applications
%@ 0975-8887
%V 11
%N 9
%P 1-5
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

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.

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Index Terms

Computer Science
Information Sciences

Keywords

Emotion categories Human computer interaction Classification Algorithms Empirical study