000 04419cam a2200505 i 4500
999 _c91756
_d91756
005 20250812104828.0
006 m o d
007 cr cnu---unuuu
008 250812s2023 njum ob u001 0 eng
020 _a9781119890942
_qhardcover
020 _a9781119890973
_qelectronic book
020 _a1119890977
_qelectronic book
020 _a9781119890966
_qelectronic book
020 _a1119890969
_qelectronic book
020 _a9781119890980
_qelectronic book
020 _a1119890985
_qelectronic book
024 7 _a10.1002/9781119890980
_2doi
035 _a(OCoLC)1348394046
037 _a9965970
_bIEEE
040 _aDLC
_beng
_erda
_cDLC
_dOCLCF
_dIEEEE
_dYDX
_dOCLCQ
041 _aeng
042 _apcc
050 0 4 _aTK7881.4
_b.L486 2023
082 0 0 _a006.4/5
_223/eng/20221018
100 1 _aLerch, Alexander,
_0https://id.loc.gov/authorities/names/n2012023114
_eauthor.
245 1 3 _aAn introduction to audio content analysis :
_bmusic information retrieval tasks & applications /
_cAlexander Lerch.
246 3 0 _aMusic information retrieval tasks and applications.
250 _aSecond edition.
264 1 _aHoboken, New Jersey :
_bJohn Wiley & Sons, Inc.,
_c©[2023]
300 _a1 online resource (xxix, 434 pages) :
_billustrations.
336 _atext
_btxt
_2rdacontent.
337 _acomputer
_bc
_2rdamedia.
338 _aonline resource
_bcr
_2rdacarrier.
340 _2rdacc
_0http://rdaregistry.info/termList/RDAColourContent/1003.
504 _aIncludes bibliographical references and index.
505 0 _aTable 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
520 _a"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"--
_cProvided by publisher.
545 0 _aAbout 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.
650 0 _aComputer sound processing.
_0https://id.loc.gov/authorities/subjects/sh85029539.
650 0 _aComputational auditory scene analysis.
_0https://id.loc.gov/authorities/subjects/sh2007000395.
650 0 _aContent analysis (Communication)
_xData processing.
_0https://id.loc.gov/authorities/subjects/sh2009121720.
655 4 _aElectronic books.
856 4 0 _uhttps://onlinelibrary.wiley.com/doi/book/10.1002/9781119890980
_yFull text is available at Wiley Online Library Click here to view
942 _2ddc
_cER