Abstract
Automatic recognition of artists is very important in acoustic music indexing, browsing, and content-based acoustic music retrieving, but synchronously it is still a challenging errand to extract the most representative and salient attributes to depict diversiform artists. In this paper, we developed a novel system to complete the reorganization of artist automatically. The proposed system can efficiently identify the artist’s voice of a raw song by analyzing substantive features extracted from both pure music and singing song mixed with accompanying music. The experiments on different genres of songs illustrate that the proposed system is possible.
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Foundation item: the National Natural Science Foundation of China (No. 60675017); the National Basic Research Program (973) of China (No. 2006CB303103)
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Zhu, Sh., Liu, Yc. Automatic artist recognition of songs for advanced retrieval. J. Shanghai Jiaotong Univ. (Sci.) 13, 513–520 (2008). https://doi.org/10.1007/s12204-008-0513-x
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DOI: https://doi.org/10.1007/s12204-008-0513-x