An old-fashioned connectionist approach to a Cajun chord change problem
István S. N. Berkeley, Roxanne B. Raine · Connection Science · 2011
In this paper, the problem of changing chords when playing Cajun music is introduced. A number of connectionist network simulations are then described, in which the networks attempted to learn to predict chord changes correctly in a particular Cajun song, ‘Bayou Pompon’. In the various sets of simulations, the amount of information provided to the network was varied. While the network had difficulty in solving the problem with six one-eighths of a bar of melody information, performance radically improved when the network was provided with seven one-eighths of a bar of melody information. A post-training analysis of a trained network revealed a ‘rule’ for solving the problem. In addition to providing useful insight for scholars interested in traditional Cajun music, the results described here also illustrate how a traditional connectionist network, trained with the familiar backpropagation learning algorithm, can be used to generate a theory of the task.