Towards efficient automated singer identification in large music databases

Authors:
Jialie Shen;Bin Cui;John Shepherd;Kian-Lee Tan
Affiliations:
The University of New South Wales, Sydney, Australia;Peking University, China;The University of New South Wales, Sydney, Australia;National University of Singapore
Venue:
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Year:
2006

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Abstract

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.