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

    3 Citations (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
    • General Computer Science

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