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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Music Emotion Classification (MEC): Exploiting Vocal and Instrumental Sound Features
verfasst von : Mudiana Mokhsin Misron, Nurlaila Rosli, Norehan Abdul Manaf, Hamizan Abdul Halim
Erschienen in: Recent Advances on Soft Computing and Data Mining
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Music conveys and evokes feeling. Many studies that correlate music with emotion have been done as people nowadays often prefer to listen to a certain song that suits their moods or emotion .This project present works on classifying emotion in music by exploiting vocal and instrumental part of a song. The final system is able to use musical features extracted from vocal part and instrumental part of a song, such as spectral centroid, spectral rolloff and zero-cross as to classify whether selected Malay popular music contain “sad” or “happy” emotion. Fuzzy
k
-NN (FKNN) and artificial neural network (ANN) are used in this system as a machine classifier. The percentages of emotion classified in Malay popular songs are expected to be higher when both features are applied.