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.
By:
Alexander Lerch
Imprint: Wiley-IEEE Press
Country of Publication: United States
Edition: 2nd edition
Dimensions:
Height: 229mm,
Width: 152mm,
Spine: 26mm
Weight: 1.211kg
ISBN: 9781119890942
ISBN 10: 1119890942
Pages: 464
Publication Date: 14 November 2022
Audience:
Professional and scholarly
,
Undergraduate
Format: Hardback
Publisher's Status: Active
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
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.
