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194.039 Intelligent Audio and Music Analysis
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2018W, VU, 3.0h, 4.5EC


  • Semester hours: 3.0
  • Credits: 4.5
  • Type: VU Lecture and Exercise

Aim of course

This class covers basics and selected applications in the areas of intelligent audio and music analysis. After completing the class, students are enabled to independently investigate topics dealing with the analysis of acoustic data and pattern mining therein and apply machine learning and information retrieval methods to recorded audio for extraction or deduction of semantic information.

Subject of course

Selected topics from the areas of acoustic signal processing, auditory scene analysis, and music information retrieval are presented and discussed, comprising the following:

- Fundamentals of audio processing, analysis, and description
- Audio event detection and classification
- Detection and tracking of musical events
- Tracking of musical concepts (e.g., beats, meter, key)
- Instrument detection and transcription
- Real-time tracking of audio events
- Music genre classification and tagging
- Multi-modality in semantic music description
- Music retrieval and recommendation

Topics are contextualized historically, giving an overview of the development from hand-crafted features to recent deep learning based methods, including convolutional and recurrent neural networks. Emphasis is given to aspects of evaluation, such as used metrics and ground truth construction. Understanding of theoretical concepts is deepened through accompanying applied lab exercises.

Additional information

ECTS Breakdown: 3.0h = 4.5 ECTS = 112.5 hours
  • 20.0h – lectures
  • 66.5h – practical tasks
  • 25.0h – preparation for examination
  •  1.0h – written examination



Course dates

Wed14:00 - 16:0010.10.2018 - 23.01.2019Seminarraum 107/1 Lecture
Intelligent Audio and Music Analysis - Single appointments
Wed10.10.201814:00 - 16:00Seminarraum 107/1 Lecture
Wed17.10.201814:00 - 16:00Seminarraum 107/1 Lecture
Wed24.10.201814:00 - 16:00Seminarraum 107/1 Lecture
Wed31.10.201814:00 - 16:00Seminarraum 107/1 Lecture
Wed07.11.201814:00 - 16:00Seminarraum 107/1 Lecture
Wed14.11.201814:00 - 16:00Seminarraum 107/1 Lecture
Wed21.11.201814:00 - 16:00Seminarraum 107/1 Lecture
Wed28.11.201814:00 - 16:00Seminarraum 107/1 Lecture
Wed05.12.201814:00 - 16:00Seminarraum 107/1 Lecture
Wed12.12.201814:00 - 16:00Seminarraum 107/1 Lecture
Wed19.12.201814:00 - 16:00Seminarraum 107/1 Lecture
Wed09.01.201914:00 - 16:00Seminarraum 107/1 Lecture
Wed16.01.201914:00 - 16:00Seminarraum 107/1 Lecture
Wed23.01.201914:00 - 16:00Seminarraum 107/1 Lecture

Examination modalities


  • 3 practical tasks and a written exam at the end of the semester. 
  • Each task, as well as the exam, contribute 25% to the final grade. 
  • On each task, at least 30% of maximum points need to be achieved to pass.

Course registration

Not necessary



No lecture notes are available.