This class is usually taught in the summer term. The class is taught in English.
Information for the current semester (if available):
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The course will start with brief introductions to Musicology and Signal Processing. Prior knowledge in these areas may be helpful but is not a requirement.
As a participant in this course, you will become familiar with several music audio analysis problems. For each, you will learn about proposed solutions using signal processing, classical algorithms and/or machine learning. A practical project will allow you to experiment with and combine the methods you learned and strengthen your problem solving skills as an individual and teammate. You will be ready to understand and tackle other audio analysis tasks.
The course is structured along different tasks in the automatic analysis of music audio via computer algorithms. These tasks include:
Lectures take place weekly in Linz. Physical attendance is highly welcome, but purely remote participation is possible. Presentation slides, lecture streams and/or recordings will be made available via Moodle.
During this course you will implement a prototypical music analysis system, consisting of an Onset Detector, a Beat Tracker and a Tempo Estimator (in Java, Python or a language of choice). All submitted systems will be compared against each other on a shared dataset.
At the end of the semester, there will be an open-book online exam on the course contents (available to all participants who completed the exercise track). For those who failed or could not attend the exam, individual oral exams will be coordinated with the participants as needed.