How to tell a Stairway to heaven from a Highway to hell: working with music as a data scientist

Course Description

This course will introduce you to a multidisciplinary field of music information retrieval, that deals with extracting information from audio and symbolic music representations. Would you like to know how Youtube finds out that a video has a copyrighted audio track? How does Spotify know, what music would you enjoy? How does one create a karaoke version of a song by separating the melody from the rest? In this course, you will find out the magic behind many such techniques for working with musical audio. We will also discuss the properties of the human auditory system and learn how to extract the most suitable data representations from the digital audio signal. In the second half of the course, we will discuss the application of the state of the art deep learning techniques in music information retrieval.

Course tools

  • Python
  • Jupyter notebooks
  • pandas, librosa, essentia, keras

Prerequisites

  • Linear algebra
  • Python
  • Basics of neural networks
Level of complexity of course Advance

Lecturer

Dr. Anna Aljanaki Assistant professor, University of Tartu Anna Aljanaki is a data scientist and a lecturer specializing in the MIR field. She got her Ph.D. in 2016 from Utrecht University, currently, she splits her time between academia and industry. Fields of interests: music information retrieval, data science, data engineering, music emotion recognition, music generation Contacts: [email protected]