A Hack Day for Classical Music

Classical Music + Technology = Future

What happens when musicians and software developers try to move the boundaries of what is doable and create breakthrough technologies? At the Karajan-Institute, we believe that such a goal can only be reached when lots of brilliant minds work together. This is why we have started the Classical Music Hack Day series four years ago: to build a network of researchers, data scientists and musicologists, who are all interested in linking technology and creativity.

Today we are proud to partner with the Salzburg Univerity of Applied Sciences and the Mozarteum University to bring the 4th Classical Music Hack Day to Salzburg. The Hack Day is a separate event that will take place April 8 – 9 at Salzburg University of Applied Sciences. For more information, please visit the event website at:

Classical Music Hack Day Website

FAQ

Q: What is hacking?

A: Here is what the “Internet User’s Glossary” (RFC 1392) from 1993 has to say:

hacker
      A person who delights in having an intimate understanding of the
      internal workings of a system, computers and computer networks in
      particular.  The term is often misused in a pejorative context,
      where "cracker" would be the correct term.  See also: cracker.

 

Q: Can I attend the Classical Music Hackathon?

A: Of course! Visitors can register for the presentation of hacks. If you are a musician, developer or scientist and would like to hack, register here.

Music Cognition and Big Data

The Topic

Recent developments in technology allow in-depth analysis of all available music recordings. The study of such a large body of data brings us one step closer to understanding one of the most complex human achievements: Music. Why do we make music, how did it evolve over time and how does musical taste work?

As we consume music in the age of technology, we not only receive data in form of recordings, but also create data when we listen to music. Algorithms of online music services analyze what, when and how we listen. They predict what we seem to like, and what we don’t.

This panel discusses the areas in which big data and music intersect with a focus on applications in health, life-sciences and education.

The Panelists