Mason Archival Repository Service

EEG-based Emotion Recognition with Music: A Model and Application

Show simple item record

dc.contributor.author Scavotto, Zakariyya
dc.date.accessioned 2022-11-21T14:11:09Z
dc.date.available 2022-11-21T14:11:09Z
dc.date.issued 2022-11
dc.identifier.citation Scavotto, Zakariyya. EEG-based Emotion Recognition with Music: A Model and Application. Senior Research Project, Thomas Jefferson High School for Science and Technology in Collaboration with George Mason University Neural Engineering Lab. November 2022. en_US
dc.identifier.uri http://hdl.handle.net/1920/12993
dc.description Senior Research Project, Thomas Jefferson High School for Science and Technology in Collaboration with George Mason University Neural Engineering Lab. November 2022. en_US
dc.description.abstract With the growth of music streaming, both for pleasure and other applications, such as music therapy, being able to understand how music makes someone feel has increased in importance. The goal of this study was twofold: first, create a machine learning model to predict a subject’s emotional response to music; then integrate this trained model into an application that can predict someone’s emotional response based on live data. Using support vector machines (SVMs) as the basis of the machine learning model, a model was trained to recognize the correct emotional response with 64% accuracy, and the model was successfully implemented into a demonstration web application. en_US
dc.language.iso en_US en_US
dc.rights Attribution-NonCommercial 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc/3.0/us/ *
dc.subject EEG en_US
dc.subject Emotion Recognition en_US
dc.subject Machine Learning en_US
dc.title EEG-based Emotion Recognition with Music: A Model and Application en_US
dc.type Working Paper en_US


Files in this item

The following license files are associated with this item:

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial 3.0 United States Except where otherwise noted, this item's license is described as Attribution-NonCommercial 3.0 United States

Search MARS


Browse

My Account

Statistics