Estimating Music Listener’s Emotion from Bio-signals by using CNN

Abstract

The purpose of this paper is to estimate emotions for music pieces with lyrics. We investigate whether four emotions (happy, sad, angry and relaxed) can be accurately estimated by obtained bio-signals of subjects during music listening by analyzing them with convolutional neural network. Questionnaire responses by subjects are used as the correct labels, and the four emotions are classified by each and combined. The results of the analysis show that the accuracies of the both classification methods highly exceed the chance level. It suggests the possibility of emotion estimation for music listeners by bio-signals.