Open AccessEmotion driven mood enhancing multimedia recommendation system using physiological signal
Author(s) -
N Sindhu,
Selvaraj Jayaraman,
R Anjali
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1070/1/012070
Subject(s) - sadness , computer science , anger , support vector machine , mood , feature extraction , multimedia , emotion classification , mel frequency cepstrum , speech recognition , artificial intelligence , psychology , psychiatry
This paper exhibits a proposal for developing a multimedia recommendation system that is driven by the emotion of the user. The multimedia system is designed in such a way that the user will not have to manually browse for the audio/video to be played, it will be played automatically based on the emotion. The database comprises ECG signals collected from DECAF. Anger and sadness, emotions contributing to negative mood are considered. Discrete Wavelet Transform (DWT) was used for feature extraction and classification accuracy was determined using kNN, SVM. It was found that kNN classifies better than SVM. Realtime signals of one single healthy subject were collected based on a protocol built. Multimedia recommendation system operates automatically based on the classified emotion.