-------- Original-Nachricht -------- Betreff: Call for Book Chapters - Intelligent Music Information Systems: Tools and Methodologies Datum: Fri, 11 Nov 2005 13:18:51 +1100 (EST) Von: Jialie Shen jls@cse.unsw.EDU.AU Firma: "OptimaNumerics" An: Computational Science Mailing List computational.science@lists.optimanumerics.com

CALL FOR BOOK CHAPTERS

BOOK TITLE:

Intelligent Music Information Systems: Tools and Methodologies

EDITORS:

Jialie Shen, The University of New South Wales, Australia John Shepherd, The University of New South Wales, Australia Bin Cui, National Singapore University, Singapore Ling Liu, Georgia Institute of Technology, USA

INTRODUCTION

Recently, with continued advances in information technology, there is an ever-growing amount of music data accessible from digital libraries, the World Wide Web, and peer-to-peer information systems. The development of new technology to facilitate music information retrieval and management has gained considerable momentum. Compared with data from other application domains, music information has many unique characteristics including rich semantics, huge volumes, high dimensionality and complex structure. All of these characteristics make informative retrieval, knowledge discovery and content management on music data challenging. To facilitate effective retrieval, many approaches have been proposed to describe and access musical content. Most of existing query engines provide keyword-based search over a text description used to label each music object. However, the success of such meta data-based search heavily depends on the ability to specify meaningful keywords, which may not always be possible in some cases. Other interesting alternatives are to query music databases based on low-level physical features adapted from traditional spectral analysis. While the state-of-the-art in musical feature extraction does offer some solutions via capturing specific acoustic characteristics (such as timbre, pitch and rhythm), it is far from satisfactory for the retrieval task for a number of reasons. First, most of them suffer from low retrieval accuracy due to semantic gap. Second, these kinds of music descriptors are typically high dimensional and sparse. Typically, it can lead to inefficient indexing and classification process in terms of categorization and searching time. We conjecture that there is a growing demand for the development of innovative technology that can support effective and efficient music object retrieval from large music data collections using various music features and a various combination of such features.

THE OVERALL OBJECTIVE OF THE BOOK

The main objective is to assemble together, in a single volume, contributions on the topic of modern music information retrieval and management, including tools, methodologies, theory, and frameworks. The book will provide insights into both the state-of-the-art music information retrieval issues and techniques and future trends in the field. It will also serve as a useful guide for researchers, practitioners, developers, and graduate students who are interested or involved in the design, state-of-the-art development, and deployment of in music retrieval, music data management, music knowledge discovery, and other related applications.

TARGET AUDIENCE

The primary target audience for the book includes researchers, graduate students, developers, and users who are interested in designing, using, and/or managing complex music information systems. Potential users can be music researchers, entertainers, or professionals from the music industry or amateur music lovers. The book will provide reviews of the concerned modern technology and insights for music information retrieval. It can be used as a comprehensive reference for both professional and amateur users or a text book for graduate and senior undergraduate students who are specializing or taking a course in Multimedia information systems.

Recommended topics include, but are not limited to, the following:

* Musical feature extraction/construction * Music content representation/summarisation * Classification, clustering and information visualisation * Music similarity and pattern matching * Music indexing (mono- and polyphonic music) * Music query modelling and metadata or protocols for music * Music search and web * Music searching in P2P environment * Music archives, digital libraries and collections * Automated music identification and recognition * New applications

SUBMISSION PROCEDURE

Researchers and practitioners are invited to submit a proposal not exceeding 600 words on or before January 31, 2006, clearly outlining the topic of the chapter and explaining the contribution in terms of the overall objectives set out in this book. Authors will be notified by February 28, 2006, about the status of their proposals. Full chapters are expected to be submitted by May 31, 2006. All submitted chapters will be reviewed on a double-blind peer review basis. Authors will be notified about the result of the reviews by July 15, 2006. Final accepted chapters are expected to be submitted by October 31, 2006 in MS Word format. The book is scheduled to be published by Idea Group, Inc., www.idea-group.com http://www.idea-group.com, publisher of the Idea Group Publishing, Information Science Publishing, IRM Press, CyberTech Publishing and Idea Group Reference imprints, in 2007.

IMPORTANT DATES

The schedule is as follows: Submission deadline of proposal: January 31, 2006 Notification of accepted proposal: February 28, 2006 Full chapter submission deadline: May 31, 2006 Notification of review results: July 15, 2006 Revised chapters due: August 31, 2006 Notification of Accepted Chapters: September 30, 2006 Final Submission Deadline: October 31, 2006

Submissions can be forwarded electronically to the following email address:

imis.book06@gmail.com

For inquiries, please contact editors as below:

Jialie Shen School of Computer Science and Engineering The University of New South Wales & National ICT, Australia NSW, 2052, Australia Email: jls@cse.unsw.edu.au Tel: 61-02-93856908 Fax: 61-02-93855995

John Shepherd School of Computer Science and Engineering The University of New South Wales NSW, 2052, Australia Email: jas@cse.unsw.edu.au Tel: 61-02-93856949 Fax: 61-02-93855995

Bin Cui Department of Computer Science National Singapore University 3 Science Drive 2, Singapore 117543 Email: cuibin@comp.nus.edu.sg Tel: (65) 68744774

Ling Liu College of Computing Georgia Institute of Technology 801 Atlantic Drive, Atlanta Georgia 30332-0280, USA Email: lingliu@cc.gatech.edu Tel: 01-404-3851139 fax: 01-404-8949846

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