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Real-valued feature indexing for music databases

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 that will help to retrieve the relevant music quickly. Several reports have pointed out that these features of music data can be transformed and represented in the forms of music feature strings or numeric values such that string indexing or numeric indexing is created, respectively, for music retrieval. For string indexing, there is only limited index structure (ex. suffix tree) suitable for music retrieval and it is lack of scalability. Moreover, for numeric indexing, there is only few research emphasized on this issue. The existing approaches all transform a specific length of music segments (features) into integers such that various numeric index structures can be applied (ex. R-tree, B-tree). In this approach, however, the length of query (query by example) is required to match the specific length of transformation of music data otherwise it will harm the efficiency of query processing. To address these problems, in this paper, we will present a real value transformation function for without specific length of music segment and for more flexible of query length. Our experimental results also show that the new approach outperforms existing index schemes.