Towards providing music for academic and leisurely activities of computer users

College

College of Computer Studies

Department/Unit

Software Technology

Document Type

Conference Proceeding

Source Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume

7458 LNAI

First Page

891

Last Page

894

Publication Date

10-25-2012

Abstract

This paper uses brainwaves to recognize the computer activity of the user and provides music recommendation. Twenty-three (23) hours of data collection was performed by asking the computer user to wear a device that collects electroencephalogram (EEG) signals from his brain as he performed whatever tasks he wanted to perform while listening to music. The features of the preferred song given the activity of the user is used to provide songs for the user automatically. Activities were classified as either academic or leisure. The music provision model was able to predict the music features preferred by the user with accuracy of 76%. © 2012 Springer-Verlag.

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Digitial Object Identifier (DOI)

10.1007/978-3-642-32695-0_93

Disciplines

Computer Sciences | Software Engineering

Keywords

Electroencephalography; Music—Computer programs

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