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Music Similarity and Retrieval

An Introduction to Audio- and Web-based Strategies

  • Peter Knees
  • Markus Schedl

Part of the The Information Retrieval Series book series (INRE, volume 36)

Table of contents

  1. Front Matter
    Pages i-xx
  2. Peter Knees, Markus Schedl
    Pages 1-30
  3. Content-Based MIR

    1. Front Matter
      Pages 31-31
    2. Peter Knees, Markus Schedl
      Pages 33-50
    3. Peter Knees, Markus Schedl
      Pages 51-84
    4. Peter Knees, Markus Schedl
      Pages 85-104
  4. Music Context-Based MIR

    1. Front Matter
      Pages 105-105
    2. Peter Knees, Markus Schedl
      Pages 107-132
    3. Peter Knees, Markus Schedl
      Pages 133-158
  5. User-Centric MIR

    1. Front Matter
      Pages 159-159
    2. Peter Knees, Markus Schedl
      Pages 179-211
  6. Current and Future Applications of MIR

    1. Front Matter
      Pages 213-213
    2. Peter Knees, Markus Schedl
      Pages 215-246
    3. Peter Knees, Markus Schedl
      Pages 247-254
  7. Back Matter
    Pages 255-299

About this book

Introduction

This book provides a summary of the manifold audio- and web-based approaches to music information retrieval (MIR) research. In contrast to other books dealing solely with music signal processing, it addresses additional cultural and listener-centric aspects and thus provides a more holistic view. Consequently, the text includes methods operating on features extracted directly from the audio signal, as well as methods operating on features extracted from contextual information, either the cultural context of music as represented on the web or the user and usage context of music.

Following the prevalent document-centered paradigm of information retrieval, the book addresses models of music similarity that extract computational features to describe an entity that represents music on any level (e.g., song, album, or artist), and methods to calculate the similarity between them. While this perspective and the representations discussed cannot describe all musical dimensions, they enable us to effectively find music of similar qualities by providing abstract summarizations of musical artifacts from different modalities.

The text at hand provides a comprehensive and accessible introduction to the topics of music search, retrieval, and recommendation from an academic perspective. It will not only allow those new to the field to quickly access MIR from an information retrieval point of view but also raise awareness for the developments of the music domain within the greater IR community. In this regard, Part I deals with content-based MIR, in particular the extraction of features from the music signal and similarity calculation for content-based retrieval. Part II subsequently addresses MIR methods that make use of the digitally accessible cultural context of music. Part III addresses methods of collaborative filtering and user-aware and multi-modal retrieval, while Part IV explores current and future applications of music retrieval and recommendation.>

Keywords

Music retrieval Multimedia and multimodal retrieval Sound and music computing Audio processing Recommender systems Retrieval models and ranking

Authors and affiliations

  • Peter Knees
    • 1
  • Markus Schedl
    • 2
  1. 1.Department of Computational PerceptionJohannes Kepler UniversityLinzAustria
  2. 2.Department of Computational PerceptionJohannes Kepler UniversityLinzAustria

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-662-49722-7
  • Copyright Information Springer-Verlag Berlin Heidelberg 2016
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-662-49720-3
  • Online ISBN 978-3-662-49722-7
  • Series Print ISSN 1387-5264
  • Buy this book on publisher's site
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