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Several neural network models were trained using a range of different training data, including music from various genres. The resulting neural network-based instruments were used to play brief pieces of music, which they used as input to create unique musical output.
Max, while useful for live performance and audio processing, proved to be somewhat impractical for this project. Implementing too complex of a network caused performance issues and even crashing. Because of this, smaller networks, which are less robust in their prediction abilities had to be used, producing very simplistic musical patterns.
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Risdon, Daniel Wilton, "Algorithmic Music Composition and Accompaniment Using Neural Networks" (2016). Senior Projects Spring 2016. 352.