• Title/Summary/Keyword: Multi-Feature Clustering(MFC)

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A Study on the Robust Content-Based Musical Genre Classification System Using Multi-Feature Clustering (Multi-Feature Clustering을 이용한 강인한 내용 기반 음악 장르 분류 시스템에 관한 연구)

  • Yoon Won-Jung;Lee Kang-Kyu;Park Kyu-Sik
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.3 s.303
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    • pp.115-120
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    • 2005
  • In this paper, we propose a new robust content-based musical genre classification algorithm using multi-feature clustering(MFC) method. In contrast to previous works, this paper focuses on two practical issues of the system dependency problem on different input query patterns(or portions) and input query lengths which causes serious uncertainty of the system performance. In order to solve these problems, a new approach called multi-feature clustering(MFC) based on k-means clustering is proposed. To verify the performance of the proposed method, several excerpts with variable duration were extracted from every other position in a queried music file. Effectiveness of the system with MFC and without MFC is compared in terms of the classification accuracy. It is demonstrated that the use of MFC significantly improves the system stability of musical genre classification performance with higher accuracy rate.

A Robust Content-Based Music Retrieval System

  • Lee Kang-Kyu;Yoon Won-Jung;Park Kyu-Sik
    • Proceedings of the IEEK Conference
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    • summer
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    • pp.229-232
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    • 2004
  • In this paper, we propose a robust music retrieval system based on the content analysis of music. New feature extraction method called Multi-Feature Clustering (MFC) is proposed for the robust and optimum performance of the music retrieval system. It is demonstrated that the use of MFC significantly improves the system stability of music retrieval with better classification accuracy.

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A Study on the Retrieval Speed Improvement from Content-Based Music Information Retrieval System (내용기반 음악 검색 시스템에서의 검색 속도 향상에 관한 연구)

  • Yoon Won-Jung;Park Kyu-Sik
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.1 s.307
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    • pp.85-90
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    • 2006
  • In this paper, we propose the content-based music information retrieval system with improved retrieval speed and stable performance while maintaining resonable retrieval accuracy In order to solve the in-stable system problem multi-feature clustering (MFC) is used to setup robust music DB. In addition, the music retrieval speed was improved by using the Superclass concept. Effectiveness of the system with SuperClass and without SuperClass is compared in terms of retrieval speed, accuracy and retrieval precision. It is demonstrated that the use of WC and Superclass substantially improves music retrieval speed up to $20\%\~40\%$ while maintaining almost equal retrieval accuracy.