Alexander Lerch

An Introduction to Audio Content Analysis (eBook, ePUB)

Music Information Retrieval Tasks and Applications

• Format: ePub

Produktbeschreibung

An Introduction to Audio Content Analysis Enables readers to understand the algorithmic analysis of musical audio signals with AI-driven approaches An Introduction to Audio Content Analysis serves as a comprehensive guide on audio content analysis explaining how signal processing and machine learning approaches can be utilized for the extraction of musical content from audio. It gives readers the algorithmic understanding to teach a computer to interpret music signals and thus allows for the design of tools for interacting with music. The work ties together topics from audio signal processing and machine learning, showing how to use audio content analysis to pick up musical characteristics automatically. A multitude of audio content analysis tasks related to the extraction of tonal, temporal, timbral, and intensity-related characteristics of the music signal are presented. Each task is introduced from both a musical and a technical perspective, detailing the algorithmic approach as well as providing practical guidance on implementation details and evaluation. To aid in reader comprehension, each task description begins with a short introduction to the most important musical and perceptual characteristics of the covered topic, followed by a detailed algorithmic model and its evaluation, and concluded with questions and exercises. For the interested reader, updated supplemental materials are provided via an accompanying website. Written by a well-known expert in the music industry, sample topics covered in Introduction to Audio Content Analysis include: * Digital audio signals and their representation, common time-frequency transforms, audio features * Pitch and fundamental frequency detection, key and chord * Representation of dynamics in music and intensity-related features * Beat histograms, onset and tempo detection, beat histograms, and detection of structure in music, and sequence alignment * Audio fingerprinting, musical genre, mood, and instrument classification An invaluable guide for newcomers to audio signal processing and industry experts alike, An Introduction to Audio Content Analysis covers a wide range of introductory topics pertaining to music information retrieval and machine listening, allowing students and researchers to quickly gain core holistic knowledge in audio analysis and dig deeper into specific aspects of the field with the help of a large amount of references.

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Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 464
• Erscheinungstermin: 22. November 2022
• Englisch
• ISBN-13: 9781119890973
• Artikelnr.: 66679569

Autorenporträt

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.

Inhaltsangabe

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