MRTB framework: a robust content-based music retrieval and browsing

Authors:
Kyu-Sik Park;Won-Jung Yoon;Kang-Kue Lee;Sang-Heon Oh;Ki-Man Kim
Affiliations:
Div. of Inf. & Comput. Sci., Dankook Univ., Seoul, South Korea;-;-;-;-
Venue:
IEEE Transactions on Consumer Electronics
Year:
2005

Citing 0
Cited 2

MUSIPER: a system for modeling music similarity perception based on objective feature subset selection

User Modeling and User-Adapted Interaction
Evaluation of Modeling Music Similarity Perception Via Feature Subset Selection

UM '07 Proceedings of the 11th international conference on User Modeling

Quantified Score

Hi-index	0.43

Visualization

Abstract

In this paper, we propose new content-based music retrieval and browsing system so called MRTB. New feature extraction procedure such as multi-feature clustering (MFC) is proposed for robust and optimum performance of the music retrieval system. Using MFC, we can achieve 86% of average retrieving success rate and 0.5∼0.8 sec retrieval time based on top 10 ranked list rules. User friendly graphical interface of MRTB S/W is implemented in thumbnail manner so the user can easily verify their retrieving results with some useful musical information.