A similar music retrieval scheme based on musical mood variation

Sanghoon Jun, Byeong Jun Han, Eenjun Hwang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Music evokes various human emotions or creates music moods through low level musical features. In fact, typical music consists of one or more moods and this can be used as an important factor for determining the similarity between music. In this paper, we propose a new music retrieval scheme based on the mood change pattern. For this, we first divide music clips into segments based on low level musical features. Then, we apply K-means clustering algorithm for grouping them into clusters with similar features. By assigning a unique mood symbol for each group, each music clip can be represented into a sequence of mood symbols. Then, we estimate the similarity of music based on the similarity of their musical mood sequence using the Longest Common Subsequence (LCS) algorithm. To evaluate the performance of our scheme, we carried out various experiments and measured the user evaluation. We report some of the results.

Original languageEnglish
Title of host publication2009 1st Asian Conference on Intelligent Information and Database Systems, ACIIDS 2009
Pages167-172
Number of pages6
DOIs
Publication statusPublished - 2009
Event2009 1st Asian Conference on Intelligent Information and Database Systems, ACIIDS 2009 - Dong Hoi, Viet Nam
Duration: 2009 Apr 12009 Apr 3

Publication series

NameProceedings - 2009 1st Asian Conference on Intelligent Information and Database Systems, ACIIDS 2009

Other

Other2009 1st Asian Conference on Intelligent Information and Database Systems, ACIIDS 2009
Country/TerritoryViet Nam
CityDong Hoi
Period09/4/109/4/3

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems
  • Software

Fingerprint

Dive into the research topics of 'A similar music retrieval scheme based on musical mood variation'. Together they form a unique fingerprint.

Cite this