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100310s2010 gw | s |||| 0|eng d |
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|a 9783642116742
|9 978-3-642-11674-2
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|a 10.1007/978-3-642-11674-2
|2 doi
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|a TA329-348
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|a MAT003000
|2 bisacsh
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|a 519
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|a Ra[, Zbigniew W.
|e editor.
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|a Advances in Music Information Retrieval
|c edited by Zbigniew W. Ra[, Alicja A. Wieczorkowska.
|h [electronic resource] /
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| 264 |
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg,
|c 2010.
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| 300 |
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|a 420p. 108 illus.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
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|a text file
|b PDF
|2 rda
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| 490 |
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|a Studies in Computational Intelligence,
|v 274
|x 1860-949X ;
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| 505 |
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|a Part I: Music Information Retrieval: Indexing, Representations, and Platforms -- Indexing Techniques for Non-Metric Music Dissimilarity Measures -- Clustering Driven Cascade Classifiers for Multi-Indexing of Polyphonic Music by Instruments -- Representations of Music in Ranking Rhythmic Hypotheses -- Mid-level Representations of Musical Audio Signals for Music Information Retrieval -- The Music Information Retrieval Evaluation eXchange: Some Observations and Insights -- Part II: Harmony -- Chord Analysis Using Ensemble Constraints -- BREVE: an HMPerceptron-Based Chord Recognition System -- Analysis of Chord Progression Data -- Part III: Content-based Identification and Retrieval of Musical Information -- Statistical Music Modeling aimed at Identification and Alignment -- Harmonic and Percussive Sound Separation and its Application to MIR-related Tasks -- Violin Sound Quality: Expert Judgements and Objective Measurements -- Emotion Based MIDI Files Retrieval System -- On Search for Emotion in Hindusthani Vocal Music -- Part IV: Music Similarity -- Audio Cover Song Identification and Similarity: Background, Approaches, Evaluation, and Beyond -- Multimodal Aspects of Music Retrieval: Audio, Song Lyrics - and beyond? -- Melodic Grouping in Music Information Retrieval: New Methods and Applications -- Automatic Musical Genre Classification and Artificial Immune Recognition System.
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|a 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, and Content 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.
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|a Engineering.
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|a Artificial intelligence.
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| 650 |
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|a Engineering mathematics.
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| 650 |
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|a Music.
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| 650 |
1 |
4 |
|a Engineering.
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| 650 |
2 |
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|a Appl.Mathematics/Computational Methods of Engineering.
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| 650 |
2 |
4 |
|a Artificial Intelligence (incl. Robotics).
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| 650 |
2 |
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|a Signal, Image and Speech Processing.
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| 650 |
2 |
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|a Music.
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| 700 |
1 |
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|a Wieczorkowska, Alicja A.
|e editor.
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
0 |
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|t Springer eBooks
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| 776 |
0 |
8 |
|i Printed edition:
|z 9783642116735
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| 830 |
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|a Studies in Computational Intelligence,
|v 274
|x 1860-949X ;
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| 856 |
4 |
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|u https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-11674-2
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| 912 |
# |
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|a ZDB-2-ENG
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| 950 |
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|a Engineering (Springer-11647)
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