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Controle de Estilos Musicais em Tarefa de Aprendizagem – Design, Implementação e Avaliação Empírica

Weber MartinsMurilo Borges SilvaLauro E. G. Nalini

The present study proposes, implements, and evaluates the intelligent selection of musical styles with Reinforcement Learning. The evaluation is empirical and undertaken in the context of human experimentation with chaining, a typical psychological task. Average values of group performance (number of trials, session duration and response latency) in three experimental conditions (silence, random and intelligent), at the first and fourth programmed sequences in each condition and among conditions have revealed significant reductions. In order to avoid “crisp” musical transitions, a (one-dimensional) ring is trained based on Kohonen’s Self-Organizing Maps and on a proper representation of musical styles.

http://www.lbd.dcc.ufmg.br/colecoes/sbie/2006/038.pdf

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