Towards Efficient Automated Singer Identification in Large Music Databases
Automated singer identification is important in organising, browsing and retrieving data in large music databases. In this paper, we propose a novel scheme, called Hybrid Singer Identifier (HSI), for automated singer recognition. HSI can effectively use multiple low-level features extracted from bot...
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| Main Authors: | , , , |
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| 格式: | text |
| 語言: | English |
| 出版: |
Institutional Knowledge at Singapore Management University
2006
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| 主題: | |
| 在線閱讀: | https://ink.library.smu.edu.sg/sis_research/1231 |
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| 機構: | Singapore Management University |
| 語言: | English |
| 總結: | Automated singer identification is important in organising, browsing and retrieving data in large music databases. In this paper, we propose a novel scheme, called Hybrid Singer Identifier (HSI), for automated singer recognition. HSI can effectively use multiple low-level features extracted from both vocal and non-vocal music segments to enhance the identification process with a hybrid architecture and build profiles of individual singer characteristics based on statistical mixture models. Extensive experimental results conducted on a large music database demonstrate the superiority of our method over state-of-the-art approaches. |
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