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Predicting Emotions Induced by Music Using System Identification Theory

Publish Year: 1392
Type: Conference paper
Language: English
View: 612

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ICBME20_011

Index date: 14 April 2015

Predicting Emotions Induced by Music Using System Identification Theory abstract

Modeling the emotional content of music is of great importance, since it is believed that music is capable of inducing different emotions. In this study we present an Autoregressivewith Exogenous Input (ARX) model based on system identification theory for modeling the emotional content of musicin a two dimensional emotion space and also a nonlinear Autoregressive with Exogenous Input (NARX) model to capture the nonlinear characteristics of the system. We also investigatethe causal relationship between musical features and the induced emotions by removing the autoregressive terms from the developed model. Finally A brief discussion about the most important features is presented.

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Predicting Emotions Induced by Music Using System Identification Theory authors

Mahdi Khajehim

Faculty of Biomedical Engineering Amirkabir University of Technology Tehran, Iran

Sahar Moghimi

Department of Biomedical Engineering Ferdowsi University of Mashhad Mashhad, Iran