Taking the Models back to Music Practice: Evaluating Generative Transcription Models built using Deep Learning

One of our latest JCMS authors, Bob Sturm, explores his research into transcription models – interesting stuff!

High Noon GMT

Our journal article has now appeared: Sturm and Ben-Tal, “Taking the Models back to Music Practice: Evaluating Generative Transcription Models built using Deep Learning”, Journal of Creative Music Systems 2(1), 2017.

My one-line precis: Here are five ways to evaluate a music generation model that are far more meaningful and insightful than the daft “Turing test”.

The contents of this article formed my introduction at the panel, “Issues in the Evaluation of Creative Music Systems”, at the 2nd Conference on the Simulation of Music Creativity. The panel was organised by Róisín Loughran, who also has an article about evaluation in the same journal volume. So, I include below an adaptation of my panel notes.

The topic of evaluation seems to be mentioned quite frequently in music generation as an extremely difficult thing to do, and I wonder why. There is a number of different ways to go…

View original post 1,420 more words

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