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Monday, March 6 • 3:00pm - 3:30pm
BachBot: Composing Bach Chorales using Deep Learning

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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.

avatar for Feynman Liang

Feynman Liang

Engineering Manager, Gigster
Feynman is the engineering manager at Gigster and a statistics PhD student at UC Berkeley. His research lies at the intersection between industry and academia, focusing on distributed machine learning and practical systems for deploying machine learning in production. He is a contributor to Apache Spark and a recreational producer of electronic music. During his MPhil degree at Cambridge University, he collaborated with Microsoft Research... Read More →

Monday March 6, 2017 3:00pm - 3:30pm

Attendees (7)