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Collaborative Use of Features in a Distributed System for the Organization of Music Collections

Copyright © 2008. 29 pages.
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DOI: 10.4018/978-1-59904-663-1.ch007|
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MLA

Mierswa, Ingo. "Collaborative Use of Features in a Distributed System for the Organization of Music Collections." Intelligent Music Information Systems: Tools and Methodologies. IGI Global, 2008. 147-175. Web. 22 Nov. 2014. doi:10.4018/978-1-59904-663-1.ch007

APA

Mierswa, I. (2008). Collaborative Use of Features in a Distributed System for the Organization of Music Collections. In J. Shen, J. Shepherd, B. Cui, & L. Liu (Eds.) Intelligent Music Information Systems: Tools and Methodologies (pp. 147-175). Hershey, PA: Information Science Reference. doi:10.4018/978-1-59904-663-1.ch007

Chicago

Mierswa, Ingo. "Collaborative Use of Features in a Distributed System for the Organization of Music Collections." In Intelligent Music Information Systems: Tools and Methodologies, ed. Jialie Shen, John Shepherd, Bin Cui and Ling Liu, 147-175 (2008), accessed November 22, 2014. doi:10.4018/978-1-59904-663-1.ch007

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Abstract

Today, large audio collections are stored at computers. Their organization can be supported by machine learning. This demands a more abstract representation than is the time series of audio values. We have developed a unifying framework which decomposes the complex extraction methods into their building blocks. This allows us to move beyond the manual composition of feature extraction methods. Several of the well-known features as well as some new ones have been composed automatically by a genetic learning algorithm. While this has delivered good classifications it needs long training times. Hence, we additionally follow a meta-learning approach. We have developed a method of feature transfer which exploits the similarity of learning tasks to retrieve similar feature extractions. This method achieves almost optimal accuracies while it is very efficient. Nemoz, an intelligent media management system, incorporates adaptive feature extraction and feature transfer which allows for personalized services in peer-to-peer settings.
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Complete Chapter List

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Chapter 1
Nicola Orio
Indexing is the core component of most information retrieval systems, because it allows for a compact representation of the content of a collection... Sample PDF
Content-Based Indexing of Symbolic Music Documents
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Chapter 2
George Tzanetakis
Marsyas, is an open source audio processing framework with specific emphasis on building Music Information Retrieval systems. It has been been under... Sample PDF
MARSYAS-0.2: A Case Study in Implementing Music Information Retrieval Systems
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Chapter 3
Richard L. Kline
This chapter discusses key issues of building and using a system designed to search and query a music collection through the input of the actual or... Sample PDF
Melodic Query Input for Music Information Retrieval Systems
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Chapter 4
María Ángeles Fernández de Sevilla, Luis M. Laita, Eugenio Roanes-Lozano
This chapter describes a logic and computer algebra based Expert System that automates identification and recognition of the cult music styles of... Sample PDF
An Expert System Devoted to Automated Music Identification and Recognition
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Chapter 5
Rafael Ramirez
We describe a novel approach to the task of identifying performers from their playing styles. We investigate how professional Jazz saxophonists... Sample PDF
Identifying Saxophonists from Their Playing Styles
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Chapter 6
Antonello D’Aguanno
State-of-the-art MIR issues are presented and discussed both from the symbolic and audio points of view. As for the symbolic aspects, different... Sample PDF
Tools for Music Information Retrieval and Playing
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Chapter 7
Ingo Mierswa
Today, large audio collections are stored at computers. Their organization can be supported by machine learning. This demands a more abstract... Sample PDF
Collaborative Use of Features in a Distributed System for the Organization of Music Collections
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Chapter 8
Marc Fetscherin
This chapter presents a model enabling content providers to successfully sell digital music. We show that content providers must overcome three main... Sample PDF
A P2P Based Secure Digital Music Distribution Channel: The Next Generation
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Chapter 9
Ioannis Karydis
In this chapter we present the most significant trends in recent research in the field of content-based music information retrieval in peer-to-peer... Sample PDF
Music Information Retrieval in P2P Networks
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Chapter 10
Eddie Al-Shakarchi, Ian Taylor
This chapter introduces the DART (Distributed Audio Retrieval using Triana) project as a framework for facilitating the distributed processing and... Sample PDF
DART: A Framework for Distributed Audio Analysis and Music Information Retrieval
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Chapter 11
Olivier Lartillot
This chapter offers an overview of computational research in motivic pattern extraction. The central questions underlying the topic, concerning the... Sample PDF
Motivic Pattern Extraction in Symbolic Domain
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Chapter 12
Sébastien Macé, Eric Anquetil, Bruno Bossis
This chapter deals with pen interaction and its use for musical notation composition and editing. The authors first present existing pen-based... Sample PDF
Pen-Based Interaction for Intuitive Music Composition and Editing
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Chapter 13
David A. Shamma, John Woodruff, Bryan Pardo
This chapter covers some of the challenges in storytelling with music. We describe the MusicStory system which creates music videos from personal... Sample PDF
MusicStory: An Autonomous, Personalized Music Video Creator
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Chapter 14
Adriano Baratè, Goffredo Haus, Luca A. Ludovico
In this chapter, we will analyze the heterogeneous contents involved in a comprehensive description of music, organizing them according to a... Sample PDF
Music Representation of Score, Sound, MIDI, Structure and Metadata All Integrated in a Single Multilayer Environment Based on XML
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