Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/19070
Title: Utilizing EEG Signal in Music Information Retrieval
Authors: ZHAO WEI
Keywords: Music Information Retrieval, Music Therapy, Sleep Quality Analysis, Emotion Recognition, Music recommendation, EEG
Issue Date: 3-Aug-2010
Source: ZHAO WEI (2010-08-03). Utilizing EEG Signal in Music Information Retrieval. ScholarBank@NUS Repository.
Abstract: Despite significant progresses in the field of music information retrieval (MIR), grand challenges such as the intention gap and the semantic gap still exist. Inspired by the current successes in the Brain Computer Interface (BCI), how to utilize electroencephalography (EEG) signal to solve the problems of MIR is investigated in this thesis. Two scenarios are discussed respectively: EEG-based music emotion annotation and EEG-based domain specific music recommendation. The former project addresses the problem that how to classify music clips to different emotion categories based on audiences' EEG signal when they listen to the music. The latter project presents an approach to analysis sleep quality from EEG signal as a component of an EEG-based music recommendation system which recommends music according to the user's sleep quality.
URI: http://scholarbank.nus.edu.sg/handle/10635/19070
Appears in Collections:Master's Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
ZhaoWEI.pdf6.07 MBAdobe PDF

OPEN

NoneView/Download

Page view(s)

362
checked on Dec 11, 2017

Download(s)

645
checked on Dec 11, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.