• 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