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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Bibliographic Details
Main Authors: SHEN, Jialie, Bin, Cui, John, Shepherd, Kian-Lee, TAN
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2006
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Online Access:https://ink.library.smu.edu.sg/sis_research/1231
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Institution: Singapore Management University
Language: English
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Summary: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.