Bio-inspired Audio Content-Based Retrieval Framework (B-ACRF)

Muda, N. A. (2009) Bio-inspired Audio Content-Based Retrieval Framework (B-ACRF). In: World Academy of Science Engineering and Technology, TOKYO, JAPAN.

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Content-based music retrieval generally involves analyzing, searching and retrieving music based on low or high level features of a song which normally used to represent artists, songs or music genre. Identifying them would normally involve feature extraction and classification tasks. Theoretically the greater features analyzed, the better the classification accuracy can be achieved but with longer execution time. Technique to select significant features is important as it will reduce dimensions of feature used in classification and contributes to the accuracy. Artificial Immune System (AIS) approach will be investigated and applied in the classification task. Bio-inspired audio content-based retrieval framework (B-ACRF) is proposed at the end of this paper where it embraces issues that need further consideration in music retrieval performances

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Information and Communication Technology > Department of Software Engineeering
Depositing User: Ms Noor Azilah Muda
Date Deposited: 14 Nov 2011 10:41
Last Modified: 28 May 2015 02:17
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