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Fundamentals of music processing: using python and jupyter notebooks

By: Muller, MeinardMaterial type: TextTextPublication details: Switzerland Springer 2021 Edition: 2ndDescription: xxxi, 495 pISBN: 9783030698102Subject(s): Computer sound processing | Electronic music | Sound--Recording and reproducing--Digital techniques | Fourier analysisDDC classification: 006.4 Summary: About this book The textbook provides both profound technological knowledge and a comprehensive treatment of essential topics in music processing and music information retrieval (MIR). Including numerous examples, figures, and exercises, this book is suited for students, lecturers, and researchers working in audio engineering, signal processing, computer science, digital humanities, and musicology. The book consists of eight chapters. The first two cover foundations of music representations and the Fourier transform—concepts used throughout the book. Each of the subsequent chapters starts with a general description of a concrete music processing task and then discusses—in a mathematically rigorous way—essential techniques and algorithms applicable to a wide range of analysis, classification, and retrieval problems. By mixing theory and practice, the book’s goal is to offer detailed technological insights and a deep understanding of music processing applications.
List(s) this item appears in: IT & Decision Sciences | Finance & Accounting
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Item type Current library Collection Call number Copy number Status Date due Barcode
Book Book Indian Institute of Management LRC
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IT & Decisions Sciences 006.4 MUL (Browse shelf(Opens below)) 1 Available 002808

About this book
The textbook provides both profound technological knowledge and a comprehensive treatment of essential topics in music processing and music information retrieval (MIR). Including numerous examples, figures, and exercises, this book is suited for students, lecturers, and researchers working in audio engineering, signal processing, computer science, digital humanities, and musicology.



The book consists of eight chapters. The first two cover foundations of music representations and the Fourier transform—concepts used throughout the book. Each of the subsequent chapters starts with a general description of a concrete music processing task and then discusses—in a mathematically rigorous way—essential techniques and algorithms applicable to a wide range of analysis, classification, and retrieval problems. By mixing theory and practice, the book’s goal is to offer detailed technological insights and a deep understanding of music processing applications.

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