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Emotion recognition using mobile phones
The availability of built-in sensors in mobile phones has enabled a host of innovative applications. One class of application deals with detecting a user's emotions. Previous applications have primarily relied on recording and displaying self-reported emotions. This paper presents an intelligen...
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Published in: | Computers & electrical engineering 2017-05, Vol.60, p.1-13 |
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creator | Zualkernan, I. Aloul, F. Shapsough, S. Hesham, A. El-Khorzaty, Y. |
description | The availability of built-in sensors in mobile phones has enabled a host of innovative applications. One class of application deals with detecting a user's emotions. Previous applications have primarily relied on recording and displaying self-reported emotions. This paper presents an intelligent emotion detection system for mobile phones implemented as a smart keyboard that infers a user's emotional state using machine learning techniques. The system uses accelerometer readings and various aspect of typing behavior like speed and delay between letters to train a classifier to predict emotions. Naïve Bayes, J48, IBK, Multi-response linear regression and SVM were evaluated and J48 was found to be the best classifier with over 90% accuracy and precision. In addition to providing emotive feedback to individual users, the system also uses geo-tagged data to collect and display emotional states of regions or countries through a website. |
doi_str_mv | 10.1016/j.compeleceng.2017.05.004 |
format | article |
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subjects | Accelerometers Bayesian analysis Cellular telephones Classifiers Emotion recognition Emotions Machine intelligence Machine learning Mobile phones Sensors Time lag |
title | Emotion recognition using mobile phones |
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