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Advances in music information retrieval

✍ Scribed by Rainer Typke, Agatha Walczak-Typke (auth.), Zbigniew W. RaΕ›, Alicja A. Wieczorkowska (eds.)


Publisher
Springer-Verlag Berlin Heidelberg
Year
2010
Tongue
English
Leaves
423
Series
Studies in Computational Intelligence 274
Edition
1
Category
Library

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✦ Synopsis


Sound waves propagate through various media, and allow communication or entertainment for us, humans. Music we hear or create can be perceived in such aspects as rhythm, melody, harmony, timbre, or mood. All these elements of music can be of interest for users of music information retrieval systems. Since vast music repositories are available for everyone in everyday use (both in private collections, and in the Internet), it is desirable and becomes necessary to browse music collections by contents. Therefore, music information retrieval can be potentially of interest for every user of computers and the Internet. There is a lot of research performed in music information retrieval domain, and the outcomes, as well as trends in this research, are certainly worth popularizing. This idea motivated us to prepare the book on Advances in Music Information Retrieval.

It is divided into four sections: MIR Methods and Platforms, Harmony, Music Similarity, andContent Based Identification and Retrieval. Glossary of basic terms is given at the end of the book, to familiarize readers with vocabulary referring to music information retrieval.

✦ Table of Contents


Front Matter....Pages -
Front Matter....Pages 1-1
Indexing Techniques for Non-metric Music Dissimilarity Measures....Pages 3-17
Clustering Driven Cascade Classifiers for Multi-indexing of Polyphonic Music by Instruments....Pages 19-38
Representations of Music in Ranking Rhythmic Hypotheses....Pages 39-64
Mid-level Representations of Musical Audio Signals for Music Information Retrieval....Pages 65-91
The Music Information Retrieval Evaluation eXchange: Some Observations and Insights....Pages 93-115
Front Matter....Pages 117-117
Chord Analysis Using Ensemble Constraints....Pages 119-142
BREVE: An HMPerceptron-Based Chord Recognition System....Pages 143-164
Analysis of Chord Progression Data....Pages 165-184
Front Matter....Pages 185-185
Statistical Music Modeling Aimed at Identification and Alignment....Pages 187-212
Harmonic and Percussive Sound Separation and Its Application to MIR-Related Tasks....Pages 213-236
Violin Sound Quality: Expert Judgements and Objective Measurements....Pages 237-260
Emotion Based MIDI Files Retrieval System....Pages 261-284
On Search for Emotion in Hindusthani Vocal Music....Pages 285-304
Front Matter....Pages 305-305
Audio Cover Song Identification and Similarity: Background, Approaches, Evaluation, and Beyond....Pages 307-332
Multimodal Aspects of Music Retrieval: Audio, Song Lyrics – and Beyond?....Pages 333-363
Melodic Grouping in Music Information Retrieval: New Methods and Applications....Pages 364-388
Automatic Musical Genre Classification and Artificial Immune Recognition System....Pages 390-402
Back Matter....Pages -

✦ Subjects


Appl.Mathematics/Computational Methods of Engineering; Artificial Intelligence (incl. Robotics); Signal, Image and Speech Processing; Music


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