An adaptation framework for QBH-based music retrieval

Seungmin Rho, Byeong Jun Han, Eenjun Hwang, Minkoo Kim

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

1 Citation (Scopus)

Abstract

In this paper, we present a new music query transcription and refinement scheme for efficient music retrieval. For the accurate music query transcription into symbolic representation, we propose a method called WAE for note onset detection, and DTC for ADF onset detection. Also, in order to improve the retrieval performance, we propose a new relevance feedback scheme using genetic algorithm. We have built a prototype system based on this scheme and performed various experiments. Experimental results show that our proposed scheme achieves a good performance.

Original languageEnglish
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems
Subtitle of host publicationKES 2007 - WIRN 2007 - 11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, Proceedings
PublisherSpringer Verlag
Pages596-603
Number of pages8
EditionPART 1
ISBN (Print)9783540748175
DOIs
Publication statusPublished - 2007
Event11th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2007, and 17th Italian Workshop on Neural Networks, WIRN 2007 - Vietri sul Mare, Italy
Duration: 2007 Sept 122007 Sept 14

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume4692 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other11th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2007, and 17th Italian Workshop on Neural Networks, WIRN 2007
Country/TerritoryItaly
CityVietri sul Mare
Period07/9/1207/9/14

Keywords

  • Genetic algorithm
  • Music retrieval
  • Relevance feedback

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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