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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Fang-Fei Kuo Man-Kwan Shan |
| Copyright Year | 2004 |
| Description | Author affiliation: Dept. of Comput. Sci. & Inf. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan (Fang-Fei Kuo) |
| Abstract | With the growth of digital music, content-based music retrieval (CBMR) has attracted increasingly attention. For most CBMR systems, the task is to return music objects similar to query in syntactic properties such as pitch and interval contour sequence. These approaches provide users the capability to look for music that has been heard. However, sometimes, listeners are looking, not for music they have been known, but for music that is new to them. Moreover, people sometimes want to retrieve music that "feels like" another music object or a music style. To the best of our knowledge, no published work investigates the content-based music style retrieval. This paper describes an approach for CBMR by melody style. We proposed four types of query specification for melody style query. The output of the melody style query is a music list ranked by the degree of relevance, in terms of music style, to the query. We developed the melody style mining algorithm to obtain the melody style classification rules. The style ranking is determined by the style classification rules. The experiment showed the proposed approach provides a satisfactory way for query by melody style. |
| Sponsorship | ACM SIGIR ACM SIGWEB IEEE Tech. Committee for Digital Libraries |
| Starting Page | 243 |
| Ending Page | 251 |
| File Size | 566357 |
| Page Count | 9 |
| File Format | |
| ISBN | 1581138326 |
| DOI | 10.1109/JCDL.2004.240042 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-06-11 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Association for Computing Machinery, Inc. (ACM) |
| Subject Keyword | Multiple signal classification Music information retrieval Content based retrieval Computer science Databases Art Application software Data mining Software libraries Computer interfaces |
| Content Type | Text |
| Resource Type | Article |
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