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Fundamentals of Music Processing - Using Python and Jupyter Notebooks (Hardcover, 2nd ed. 2021)
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Fundamentals of Music Processing - Using Python and Jupyter Notebooks (Hardcover, 2nd ed. 2021)
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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.
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