DocumentCode
1629618
Title
HSI: A Novel Framework for Efficient Automated Singer Identification in Large Music Database
Author
Shen, Jialie ; Shepherd, John ; Cui, Bin ; Tan, Kian-Lee
Author_Institution
UNSW, Australia
fYear
2006
Firstpage
169
Lastpage
169
Abstract
The singer’s information is essential in organising, browsing and exploring music data. As an important component of music database systems, the automated artist identification is gaining considerable momentum due to numerous potential applications including music indexing and retrieval, copy right management and music recommendation systems. Unfortunately, the most currently employed approaches are still in their infancy and the performance is by far less satisfactory. Indeed, they suffer from low effectiveness, less robustness and poor scalability to accommodate large scale of data. In this demo, we presents a novel system, called Hybrid Singer Identifier (HSI), for efficient and effective automated singer identification in large music databases.
Keywords
Australia; Database systems; Delay; Indexing; Large-scale systems; Multiple signal classification; Music information retrieval; Noise robustness; Recommender systems; Scalability;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Engineering, 2006. ICDE '06. Proceedings of the 22nd International Conference on
Print_ISBN
0-7695-2570-9
Type
conf
DOI
10.1109/ICDE.2006.79
Filename
1617537
Link To Document