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Musik Information Retrieval

Winter

(engl. Music Information Retrieval )

Modulnummer: FIN-INF-120516
Link zum LSF: LSF
Verantwortung: Sebastian Stober
Dozent:in: Sebastian Stober
Lehrveranstaltungen:
  • Vorlesung Musik Information Retrieval
  • Übung Musik Information Retrieval
Verwendbarkeit: - M.Sc. INF: Informatik
- M.Sc. INGINF: Informatik
- M.Sc. WIF: Informatik
- M.Sc. DKE: Applied Data Science
- M.Sc. DE: Grundlagen Informatik
- M.Sc. VC: Computer Science

Kürzel

MIR

CP

6

Semester

Winter

Fachsem.

ab 1.

Dauer

1 Semester

Sprache

deutsch

Niveau

Master

Angestrebte Lernergebnisse:
The students ...

  • know the basics of digital music processing
  • know different music formats (representations) and relevant characteristics
  • are able to analyze and model problems of music analysis with the help of theories and methods of computer science
  • can implement and test computer-aided solutions for the analysis of music data (e.g. music synchronization, structural analysis, content-based retrieval, source separation)

Inhalt:

  • Music Representations
  • Fourier Analysis of Signals
  • Music Synchronization
  • Music Structure Analysis
  • Chord Recognition
  • Tempo and Beat Tracking
  • Content-Based Audio Retrieval
  • Musically Informed Audio Decomposition

Arbeitsaufwand:

  • Attendance time = 56 hours
  • Independent work = 124 hours: Preparation and follow-up of lectures and exercises, working on exercises and programming tasks, course project

Prüfungsvorleistungen: Studien-/Prüfungsleistungen: Lehrform / SWS:

Oral examination: Announcement of the necessary preliminary work in the first week of the course and on the lecture website; Schein (oral): Announcement of the necessary preliminary work in the first week of the course and on the lecture website

  • Lecture (2 SWS)
  • Exercise (2 SWS)

Voraussetzungen nach Prüfungsordnung: Empfohlene Voraussetzungen:

none


Medienformen: Literatur:


Meinard Müller: Fundamentals of Music Processing Using Python and Jupyter Notebooks 2nd edition, Springer 2021 ISBN: 978-3-030-69807-2

Hinweise: