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[P] Composing Bach Chorales Using Deep Learning

This is a 30 minute talk from GOTO Copenhagen 2019 by Feynman Liang – Creator of BachBot. I’ve dropped the full talk abstract below for a read before diving into the talk:

Can musical creativity, something believed to be deeply human, be codified into an algorithm?

While most music theorists are hesitant to claim a “correct” algorithm for composing music like Bach, recent advances in machine learning and computational musicology may help us reach an answer.

In this talk, we describe BachBot: an artificial intelligence which uses deep learning and long short term memory (LSTM) to compose music in the style of Bach. We train BachBot on all known Bach chorale harmonisations and carry out the largest musical Turing test to date. Our results show that the average listener can distinguish BachBot from real Bach only 5% better than random guessing, suggesting that algorithmic composition of Bach chorales is more closed (as a result of BachBot) than open a problem.

What will the audience learn from this talk? How we trained AI to compose music most people cannot tell apart from Bach’s own chorales, and the (not so) surprising discoveries along the way.

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.