Fundamentals of Music Processing

Using Python and Jupyter Notebooks
2. Auflage 2021
ISBN: 978-3-030-69807-2
Verlag: Springer International Publishing

Buch, Englisch, 495 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 1047 g

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.

Asa 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.

Zielgruppe

Graduate

Autoren/Hrsg.

Müller, Meinard

Fachgebiete

• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Akustik, Tontechnik
• Geisteswissenschaften Musikwissenschaft Musikwissenschaft Allgemein Musikalische Akustik, Tontechnik, Musikaufnahme
• Mathematik | Informatik EDV | Informatik Informatik Tonsignalverarbeitung
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Signalverarbeitung, Bildverarbeitung, Scanning
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Information Retrieval

Inhaltsverzeichnis

1. Music Representations.- 2. Fourier Analysis of Signals.- 3. Music Synchronization.- 4. Music Structure Analysis.- 5. Chord Recognition.- 6. Tempo and Beat Tracking.- 7. Content-Based Audio Retrieval.- 8. Musically Informed Audio Decomposition.

Über Autor(innen)

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.