Recurrent Neural Networks and Pitch Representations for Music Tasks

We present results from experiments in using several pitch representations for jazz-oriented musical tasks performed by a recurrent neural network. We have run experiments with several kinds of recurrent networks for this purpose, and have found that Long Short-term Memory networks provide the best results. We show that a new pitch representation called Circles of Thirds works as well as two other published representations for these tasks, yet it is more succinct and enables faster learning. Recurrent Neural Networks and Music Many researchers are familiar with feedforward neural networks consisting of 2 or more layers of processing units, each with weighted connections to the next layer. Each unit passes the sum of its weighted inputs through a nonlinear sigmoid function. Each layer's outputs are fed forward through the network to the next layer, until the output layer is reached. Weights are initialized to small initial random values. Via the back-propagation algorithm (Rumelha...

• Type: Conference
• Year: 2004
• Where: FLAIRS
• Authors: Judy A. Franklin
• Keywords: Artificial Intelligence, FLAIRS 2004, Pitch Representation, Recurrent Network, Recurrent Neural Networks