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IJSTR >> Volume 5 - Issue 6, June 2016 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Extraction Of Audio Features For Emotion Recognition System Based On Music

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Kee Moe Han, Theingi Zin, Hla Myo Tun



Vocalist’s emotion, Audio features, MIR tool box, English songs, Emotion recognition system.



Music is the combination of melody, linguistic information and the vocalist’s emotion. Since music is a work of art, analyzing emotion in music by computer is a difficult task. Many approaches have been developed to detect the emotions included in music but the results are not satisfactory because emotion is very complex. In this paper, the evaluations of audio features from the music files are presented. The extracted features are used to classify the different emotion classes of the vocalists. Musical features extraction is done by using (Music Information Retrieval) MIR tool box in this paper. The database of 100 music clips are used to classify the emotions perceived in music clips. Music may contain many emotions according to the vocalist’s mood such as happy, sad, nervous, bored, peace etc. In this paper, the audio features related to the emotions of the vocalists are extracted to use in emotion recognition system based on music.



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