Fundamentals of Music Processing : Using Python and Jupyter Notebooks

Meinard Müller

ISBN 10: 3030698106 / ISBN 13: 9783030698102

Published by Springer, Springer, 2022

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.As a substantial extension, the textbook s second edition introduces the FMP (fundamentals of music processing) not Elektronisches Buch, which provide additional audio-visual material and Python code examples that implement all computational approaches step by step. Using Jupyter not Elektronisches Buch and open-source web applications, the FMP not Elektronisches Buch yield an interactive framework that allows students to experiment with their music examples, explore the effect of parameter settings, and understand the computed results by suitable visualizations and sonifications. The FMP not Elektronisches Buch are available from the author s institutional web page at the International Audio Laboratories Erlangen.

Seller Inventory # 9783030698102

Bibliographic Details

• Title: Fundamentals of Music Processing : Using Python and Jupyter Notebooks
• Publisher: Springer, Springer
• Publication Date: 2022
• Language: English
• ISBN 10: 3030698106
• ISBN 13: 9783030698102
• Binding: Taschenbuch
• Edition: 2nd Edition
• Condition: Neu
• Dimensions: 235W x 155H x 27D millimeters 235 millimeters width by 155 millimeters height by 27 millimeters depth
• Weight: 887 grams

About this title

Synopsis

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.

 

As a substantial extension, the textbook’s second edition introduces the FMP (fundamentals of music processing) notebooks, which provide additional audio-visual material and Python code examples that implement all computational approaches step by step. Using Jupyter notebooks and open-source web applications, the FMP notebooks yield an interactive framework that allows students to experiment with their music examples, explore the effect of parameter settings, and understand the computed results by suitable visualizations and sonifications. The FMP notebooks are available from the author’s institutional web page at the International Audio Laboratories Erlangen.

 

 

 

About the Author

Meinard Müller is professor for Semantic Audio Processing at the International Audio Laboratories Erlangen, Germany, a joint institution of the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and the Fraunhofer Institute for Integrated Circuits IIS. His research interests include music processing, music information retrieval, audio signal processing, content-based multimedia, and motion retrieval.