Universität Wien

160080 UE Introduction to Python with Applications in Music Information Retrieval and Sound Analysis (2022S)

5.00 ECTS (2.00 SWS), SPL 16 - Musikwissenschaft und Sprachwissenschaft
Prüfungsimmanente Lehrveranstaltung
GEMISCHT
Moodle

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 30 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

  • Freitag 25.03. 15:00 - 16:30 Digital
  • Samstag 09.04. 09:45 - 13:00 Hörsaal 1 Musikwissenschaft UniCampus Hof 9, 3G-EG-09
  • Samstag 09.04. 14:00 - 17:15 Hörsaal 1 Musikwissenschaft UniCampus Hof 9, 3G-EG-09
  • Montag 23.05. 09:45 - 11:15 Digital
  • Samstag 11.06. 09:45 - 13:00 Hörsaal 1 Musikwissenschaft UniCampus Hof 9, 3G-EG-09
  • Samstag 11.06. 14:00 - 17:15 Hörsaal 1 Musikwissenschaft UniCampus Hof 9, 3G-EG-09
  • Freitag 24.06. 15:00 - 18:15 Hörsaal 1 Musikwissenschaft UniCampus Hof 9, 3G-EG-09
  • Samstag 25.06. 09:45 - 13:00 Hörsaal 1 Musikwissenschaft UniCampus Hof 9, 3G-EG-09
  • Samstag 25.06. 14:00 - 15:30 Hörsaal 1 Musikwissenschaft UniCampus Hof 9, 3G-EG-09

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

This is an introductory course on the Python programming language focusing on applications for music Information Retrieval and sound Analysis. The students will acquire knowledge of basic computer data structures, programming and debugging techniques, open software principles, signal processing with a focus on digital audio, and data visualization techniques. The students will gain practical skills in using Jupyter Notebooks and the version control software Git. Furthermore, they will gain working knowledge of two open-source libraries for sound analysis: the Librosa python package and the Essentia library.

The course is designed to enable students to carry out research projects within the fields of music and audio analysis.

The course format includes lectures, practical courses and exercises in Python. The students will create python scripts to perform specific audio analysis and visualize the results. They will be encouraged to work in group projects using free GitHub accounts for version control.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Assessment will be graded based on completion of homework assignments (30%) and a final project (70%).

Mindestanforderungen und Beurteilungsmaßstab

It is intended for students attending a Master’s or a Bachelor’s program in musicology and requires basic understanding of acoustics. However, it does not require any prior knowledge in computer programming.

Prüfungsstoff

Literatur

Müller, M. (2021). Fundamentals of Music Processing Using Python and Jupyter Notebooks. Springer International Publishing. https://doi.org/10.1007/978-3-030-69808-9

McFee, B., Raffel, C., Liang, D., Ellis, D., McVicar, M., Battenberg, E., & Nieto, O. (2015). librosa: Audio and Music Signal Analysis in Python. Proceedings of the 14th Python in Science Conference, Scipy, 18–24. https://doi.org/10.25080/majora-7b98e3ed-003

Steiglitz, K. (1997). A Digital Signal Processing Primer: With Applications to Digital Audio and Computer Music. Addison Wesley Longman Publishing Co. Inc.

Zuordnung im Vorlesungsverzeichnis

BA: SYS-V, INT, FRE
MA: M02, M03, M05, M09, M17

EC DH: DH2
MA DH: S-DH Cluster V - Musik

Letzte Änderung: Do 11.05.2023 11:27