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6th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2007)
Hybrid Multi-Feature Indexing for Music Data Retrieval
Melbourne, Australia
July 11-July 13
ISBN: 0-7695-2841-4
Yu-lung Lo, Chaoyang University of Technology, Taiwan
Chun-hsiung Wang, Chaoyang University of Technology, Taiwan
The management of large collections of music data in a multimedia database has received much attention in the past few years. In the most of current works, the researchers extract the features, such as melodies, rhythms and chords, from the music data and develop indices for helping to retrieve the relevant music efficiently. However, there is only a small number of existing approaches introduced multi-feature index structures for music queries while most of researches are for developing single feature indices. The existing music multi-feature index structures are memory consuming and lack of scalability. In this paper, we will propose a hybrid index structure which can save lots of memory for music multi-feature indexing. Our experimental results also show that the new approach outperforms existing multi-feature index scheme for memory needed.
Citation:
Yu-lung Lo, Chun-hsiung Wang, "Hybrid Multi-Feature Indexing for Music Data Retrieval," icis, pp.543-548, 6th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2007), 2007
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