InMAF: Indexing Music Databases via Multiple Acoustic Features
Conference Proceeding Article
Music information processing has become very important due to the ever-growing amount of music data from emerging applications. In this demonstration, we present a novel approach for generating small but comprehensive music descriptors to facilitate efficient content music management (accessing and retrieval, in particular). Unlike previous approaches that rely on low-level spectral features adapted from speech analysis technology, our approach integrates human music perception to enhance the accuracy of the retrieval and classification process via PCA and neural networks. The superiority of our method is demonstrated by comparing it with state-of-the-art approaches in the areas of music classification query effectiveness, and robustness against various audio distortion/alternatives.
Databases and Information Systems | Numerical Analysis and Scientific Computing
Data Management and Analytics
SIGMOD '06 Proceedings of the 2006 ACM SIGMOD international conference on management of data
SHEN, Jialie; Shepherd, John; and Ngu, AHH.
InMAF: Indexing Music Databases via Multiple Acoustic Features. (2006). SIGMOD '06 Proceedings of the 2006 ACM SIGMOD international conference on management of data. 778-780. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1232
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