Scalable multi-feature index structure for music databases

  • Authors:

  • Yu-Lung Lo;Chu-Hui Lee;Chun-Hsiung Wang

  • Affiliations:

  • Department of Information Management, Chaoyang University of Technology, Taichung County 413, Taiwan;Department of Information Management, Chaoyang University of Technology, Taichung County 413, Taiwan;Department of Information Management, Chaoyang University of Technology, Taichung County 413, Taiwan

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2009

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Abstract

The management of large collections of music data in a multimedia database has received much attention in the past few years. In the majority of current work, researchers extract the features, such as melodies, rhythms, and chords, from the music data and develop indices that will help to retrieve the relevant music quickly. Several reports have pointed out that these music features can be transformed and represented in forms of music feature strings or numeric values so that indices can be created for music retrieval. However, there are only a small number of existing approaches which introduce multi-feature index structures for music queries while most of the others are for developing single feature indices. The existing music multi-feature index structures are memory consuming and have lack of scalability. In this paper, we will propose a two-tier music index structure which is an efficient and scalable approach for multi-feature music indexing. Our experimental results show that this new approach outperforms existing multi-feature index schemes.