Title :
Music Mood Classification Using Intro and Refrain Parts of Lyrics
Author :
Seungwon Oh ; Minsoo Hahn ; Jinsul Kim
Author_Institution :
Digital Media Lab., Korea Adv. Inst. of Sci. & Technol. (KAIST), Daejeon, South Korea
Abstract :
In this paper, we propose an lyrics-based classification approach. It estimates a mood of a song with only intro and refrain parts of lyrics. In general, the intro part creates a specific atmosphere of a song, and the chorus part is the strongest part of the song. The proposed method detects important features significantly associated with the mood of songs from the both parts. By calculating the similarity between terms of the parts and eight basic emotions, it can classify songs according to mood.
Keywords :
emotion recognition; feature extraction; music; pattern classification; text analysis; chorus part; emotion; feature detection; lyrics intro part; lyrics refrain part; lyrics-based classification; music mood classification; song atmosphere; song mood estimation; Accuracy; Atmosphere; Media; Mood; Music; Speech; Speech recognition;
Conference_Titel :
Information Science and Applications (ICISA), 2013 International Conference on
Conference_Location :
Suwon
Print_ISBN :
978-1-4799-0602-4
DOI :
10.1109/ICISA.2013.6579495