Effective content-based music retrieval with pattern-based relevance feedback

Ja Hwung Su, Tzu Shiang Hung, Chun Jen Lee, Chung Li Lu, Wei Lun Chang, Vincent Shin-Mu Tseng*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

To retrieve the preferred music piece from a music database, contentbased music retrieval has been studied for several years. However, it is not easy to retrieve the desired music pieces within only one query process. It motivates us to propose a novel query refinement technique called PBRF (Pattern-based Relevance Feedback) to predict the user's preference on music via a series of feedbacks, which combines three kinds of query refinement strategies, namely QPM (Query Point Movement), QR (Query Reweighting) and QEX (Query Expansion). In this work, each music piece is transformed into a pattern string, and the related discriminability and representability of each pattern can be calculated then. According to the information of discriminability and representability calculated, the user's preference on music can be retrieved by matching patterns of music pieces in the music database with those of a query music piece. In addition, with considering the local-optimal problem, extensive and intensive search methods based on user's feedbacks are proposed to approximate the successful search. Through the integration of QPM, QR, QEX and switch-based search strategies, the user's intention can be captured more effectively. The experimental results reveal that our proposed approach performs better than existing methods in terms of effectiveness.

Original languageEnglish
Title of host publicationKnowledge-Based and Intelligent Information and Engineering Systems - 15th International Conference, KES 2011, Proceedings
Pages285-295
Number of pages11
EditionPART 2
DOIs
StatePublished - 29 Sep 2011
Event15th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2011 - Kaiserslautern, Germany
Duration: 12 Sep 201114 Sep 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6882 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2011
CountryGermany
CityKaiserslautern
Period12/09/1114/09/11

Keywords

  • Content-based music retrieval
  • pattern-based relevance feedback
  • query expansion
  • query point movement
  • query re-weighting

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