Real-valued Feature Indexing for Music Databases

• Main Authors: Ling-Yi Tsai, 蔡怜怡
• Other Authors: Yu-lung Lo
• Format: Others
• Language: en_US
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/48117566793609064821

碩士 === 朝陽科技大學 === 資訊管理系碩士班 === 98 === 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 research, we will present a real value transformation function for without specific length of music segment and for more flexible of query length. We also provide exact matching and fault tolerant query searching schemes for our proposed real-valued music index in this research. Our experimental results show that our new approach outperforms existing music index schemes and supports more efficiently query searching for music data retrieval. Especially, we have great improvement in fault tolerance of approximate music query.