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Advances in Music Information Retrieval

Overview of attention for book
Cover of 'Advances in Music Information Retrieval'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Indexing Techniques for Non-metric Music Dissimilarity Measures
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    Chapter 2 Clustering Driven Cascade Classifiers for Multi-indexing of Polyphonic Music by Instruments
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    Chapter 3 Representations of Music in Ranking Rhythmic Hypotheses
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    Chapter 4 Mid-level Representations of Musical Audio Signals for Music Information Retrieval
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    Chapter 5 Advances in Music Information Retrieval
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    Chapter 6 Chord Analysis Using Ensemble Constraints
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    Chapter 7 BREVE: An HMPerceptron-Based Chord Recognition System
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    Chapter 8 Analysis of Chord Progression Data
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    Chapter 9 Statistical Music Modeling Aimed at Identification and Alignment
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    Chapter 10 Harmonic and Percussive Sound Separation and Its Application to MIR-Related Tasks
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    Chapter 11 Violin Sound Quality: Expert Judgements and Objective Measurements
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    Chapter 12 Emotion Based MIDI Files Retrieval System
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    Chapter 13 On Search for Emotion in Hindusthani Vocal Music
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    Chapter 14 Audio Cover Song Identification and Similarity: Background, Approaches, Evaluation, and Beyond
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    Chapter 15 Multimodal Aspects of Music Retrieval: Audio, Song Lyrics – and Beyond?
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    Chapter 16 Melodic Grouping in Music Information Retrieval: New Methods and Applications
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    Chapter 17 Automatic Musical Genre Classification and Artificial Immune Recognition System
Attention for Chapter 10: Harmonic and Percussive Sound Separation and Its Application to MIR-Related Tasks
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Citations

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26 Mendeley
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Chapter title
Harmonic and Percussive Sound Separation and Its Application to MIR-Related Tasks
Chapter number 10
Book title
Advances in Music Information Retrieval
Published by
Springer, Berlin, Heidelberg, January 2010
DOI 10.1007/978-3-642-11674-2_10
Book ISBNs
978-3-64-211673-5, 978-3-64-211674-2
Authors

Nobutaka Ono, Kenichi Miyamoto, Hirokazu Kameoka, Jonathan Le Roux, Yuuki Uchiyama, Emiru Tsunoo, Takuya Nishimoto, Shigeki Sagayama

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 8%
Spain 1 4%
India 1 4%
Tunisia 1 4%
Unknown 21 81%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 23%
Researcher 6 23%
Student > Bachelor 5 19%
Student > Master 4 15%
Lecturer 2 8%
Other 2 8%
Unknown 1 4%
Readers by discipline Count As %
Engineering 10 38%
Computer Science 10 38%
Arts and Humanities 2 8%
Physics and Astronomy 2 8%
Earth and Planetary Sciences 1 4%
Other 0 0%
Unknown 1 4%