Title

Integrating Heterogeneous Features for Efficient Content-based Music Retrieval

Publication Type

Conference Proceeding Article

Publication Date

2004

Abstract

In this paper, we present a novel feature extraction method facilitating efficient content-based music retrieval and classification, called InMAF. The goal of our approach is to allow straightforward incorporation of multiple musical features, such as timbral texture, pitch and rhythm structure, into a single low dimensional vector that is effective for retrieval and classification. Unlike earlier approaches that used only acoustic properties as the basis for retrieval, our approach can easily incoporate human music perception to improve accuracy of retrieval and classification process. The superiority of our method is demonstrated by comparing it with state-of-the-art approaches in the areas of music classification (using a variety of machine learning algorithms), query effectiveness and robustness against audio distortion.

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Research Areas

Data Management and Analytics

Publication

CIKM '04 Proceedings of the ACM 13th Conference on Information and Knowledge Management

First Page

154

Last Page

155

ISBN

9781581138740

Identifier

10.1145/1031171.1031200

Publisher

ACM

Additional URL

http://dx.doi.org/10.1145/1031171.1031200

Comments

Poster Track

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