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Document Type

Book Chapter

Department/Unit

Department of Computer Science

Title

Adaptive indexing for semantic music information retrieval

Language

English

Abstract

With the rapid advancement of music compression and storage technologies, digital music can be easily created, shared and distributed, not only in computers, but also in numerous portable digital devices. Music often constitutes a key component in many multimedia databases, and as they grow in size and complexity, their meaningful search and retrieval become important and necessary. Music Information Retrieval (MIR) is a relatively young and challenging research area started since the late 1990s. Although some form of music retrieval is available on the Internet, these tend to be inflexible and have significant limitations. Currently, most of these music retrieval systems only rely on low-level music information contents (e.g., metadata, album title, lyrics, etc.), and in this chapter, the authors present an adaptive indexing approach to search and discover music information. Experimental results show that through such an indexing architecture, high-level music semantics may be incorporated into search strategies. © 2011, IGI Global.

Publication Date

2011

Source Publication Title

Machine learning techniques for adaptive multimedia retrieval: Technologies applications and perspectives

Editors

Wei, Chia-Hung ; Li, Yue

Start Page

287

End Page

300

Publisher

Information Science Reference

ISBN (print)

9781616928599

ISBN (electronic)

9781616928612

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