Math class teaches a computer to channel J.S. Bach | Department of Computer Science

The course was Industrial Mathematics, and the students were challenged to apply a mathematical theory to a practical problem: teaching a computer to compose music with specific style, rhythm and structure parameters, inform Anne Manning, Science Writer and Senior Public Relations Specialist.

At the end of the semester, students in the Industrial Mathematics class presented their work on using a neural network to compose music in the style of J.S. Bach.

This past semester, 11 Colorado State University master’s and Ph.D. students composed a suite of musical pieces that sound strikingly like they were written by J.S. Bach, the prolific German composer of the Baroque period.

These weren’t music students, though. They were math students.

The course was Industrial Mathematics, and the students were challenged by their professor, Michael Kirby, to apply a mathematical theory to a practical problem: teaching a computer to compose music with specific style, rhythm and structure parameters. To do it, the students used a type of machine-learning algorithm familiar to any iPhone owner who uses Siri, Apple’s voice recognition software.

What does composing music have to do with voice recognition software? It boils down to a type of neural network, called an LSTM – a long short-term memory network. Together, the class read an academic paper that explains the background of the LSTM algorithm and how it works, then Kirby asked them to reproduce the results. The students chose a Bach dataset, and created computer code to back up their results...

Broad range of uses
Kirby explained that the LSTM neural network is applicable to a wide variety of problems and datasets, and he is exploring whether LSTMs could be useful for studying a broad range of data that have more than one time-dependent variable. Music is one example of such a multivariate time series.
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Source: Department of Computer Science