Modeling Music Emotion Judgments Using Machine Learning Methods.

ABSTRACT: Emotion judgments and five channels of physiological data were obtained from 60 participants listening to 60 music excerpts. Various machine learning (ML) methods were used to model the emotion judgments inclusive of neural networks, linear regression, and random forests. Input for models of perceived emotion consisted of audio features extracted from the music recordings. Input for models of felt emotion consisted of physiological features extracted from the physiological recordings. Models were trained and interpreted with consideration of the classic debate in music emotion between cognitivists and emotivists. Our models supported a hybrid position wherein emotion judgments were influenced by a combination of perceived and felt emotions. In comparing the different ML approaches that wer

SUBMITTER: Vempala NN 

PROVIDER: S-EPMC5760560 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature