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|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||Citation:||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)|
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