TY - GEN
T1 - A similar music retrieval scheme based on musical mood variation
AU - Jun, Sanghoon
AU - Han, Byeong Jun
AU - Hwang, Eenjun
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
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U2 - 10.1109/ACIIDS.2009.65
DO - 10.1109/ACIIDS.2009.65
M3 - Conference contribution
AN - SCOPUS:70449119258
SN - 9780769535807
T3 - Proceedings - 2009 1st Asian Conference on Intelligent Information and Database Systems, ACIIDS 2009
SP - 167
EP - 172
BT - 2009 1st Asian Conference on Intelligent Information and Database Systems, ACIIDS 2009
T2 - 2009 1st Asian Conference on Intelligent Information and Database Systems, ACIIDS 2009
Y2 - 1 April 2009 through 3 April 2009
ER -