InMAF: Indexing Music Databases via Multiple Acoustic Features
Publication Type
Conference Proceeding Article
Publication Date
2006
Abstract
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.
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Publication
SIGMOD '06 Proceedings of the 2006 ACM SIGMOD international conference on management of data
First Page
778
Last Page
780
ISBN
9781595934345
Identifier
10.1145/1142473.1142587
Publisher
ACM
Citation
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.
Available at: https://ink.library.smu.edu.sg/sis_research/1232
Additional URL
http://dx.doi.org/10.1145/1142473.1142587
Comments
System Demo Track