Data Abstraction In Emotionally Tagged Models for Compositional Design in Music Running Title: Emotional Musical Data Abstraction

Abstract

In this paper, we focus on how we solve the problem of generating musical compositional designs of a particular emotional slant (happy, sad and angry) for use in the training of cognitive models. The data will provide training examples for auditory cortex and emotion modules. There are two goals to our research: first, model the process of musical compositional design for eventual use in the development of an autonomous musical composition program with a mixture of emotional content; and second, use the musical model as a quantitative means of training the auditory cortex portion and associated emotional circuits of a general model of cognition.

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Cite this paper

@inproceedings{Dzuris2003DataAI, title={Data Abstraction In Emotionally Tagged Models for Compositional Design in Music Running Title: Emotional Musical Data Abstraction}, author={Linda Dzuris and James Peterson}, year={2003} }