An introduction to audio content analysis : music information retrieval tasks & applications / Alexander Lerch.
By: Lerch, Alexander [author.]
Language: English Publisher: Hoboken, New Jersey : John Wiley & Sons, Inc., ©[2023]Edition: Second editionDescription: 1 online resource (xxix, 434 pages) : illustrationsContent type: text Media type: computer Carrier type: online resourceISBN: 9781119890942; 9781119890973; 1119890977; 9781119890966; 1119890969; 9781119890980; 1119890985Other title: Music information retrieval tasks and applicationsSubject(s): Computer sound processing | Computational auditory scene analysis | Content analysis (Communication) -- Data processingGenre/Form: Electronic books.DDC classification: 006.4/5 LOC classification: TK7881.4 | .L486 2023Online resources: Full text is available at Wiley Online Library Click here to viewItem type | Current location | Home library | Call number | Status | Date due | Barcode | Item holds |
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COLLEGE LIBRARY | COLLEGE LIBRARY | 006.4/5 (Browse shelf) | Available |
Includes bibliographical references and index.
Table of Contents
Author Biography xvii
Preface xix
Acronyms xxi
List of Symbols xxv
Source Code Repositories xxix
1 Introduction 1
Part I Fundamentals of Audio Content Analysis 9
2 Analysis of Audio Signals 11
3 Input Representation 17
4 Inference 91
5 Data 107
Part II Music Transcription 127
7 Tonal Analysis 129
8 Intensity217
9 Temporal Analysis 229
10 Alignment 281
Part III Music Identification, Classification, and Assessment 303
11 Audio Fingerprinting 305
12 Music Similarity Detection and Music Genre Classification 317
13 Mood Recognition 337
14 Musical Instrument Recognition 347
15 Music Performance Assessment 355
Part IV Appendices 365
Appendix A Fundamentals 367
Appendix B Fourier Transform 385
Appendix C Principal Component Analysis 405
Appendix D Linear Regression 409
Appendix E Software for Audio Analysis 411
Appendix F Datasets 417
Index 425
"This book explores algorithms that extract the relevant content information from a digital audio signal and interpret the extracted information for applications such as music recommendation, music tutoring, or music generation. This second edition covers an even broader range of tasks aimed at extracting all forms of musical content from the audio. After a general introduction in the process and goals of audio content analysis, the text focuses on tasks that can be grouped into a content category: tonal analysis, intensity analysis, and temporal analysis. The following chapters often span multiple of these categories and cover the alignment of two audio sequences, the classification of musical genre, mood, and instruments, the computation of music similarity, and the assessment of music performance"-- Provided by publisher.
About the Author
Alexander Lerch, PhD, is an Associate Professor at the Center for Music Technology, Georgia Institute of Technology. His research focuses on signal processing and machine learning applied to music, an interdisciplinary field commonly referred to as music information retrieval. He has authored more than 50 peer-reviewed publications and his website, www.AudioContentAnalysis.org, is a popular resource on Audio Content Analysis, providing video lectures, code examples, and other materials.
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