Towards the Automatic Recommendation of Musical Parameters based on Algorithm for Extraction of Linguistic Rules

Félix Castro Espinoza, Omar López-Ortega, Anilú Franco-Árcega


In the present article the authors describe an analysis of data associated to the emotional responses to fractal generated music. This analysis is done via discovery of rules, and it constitutes the basis to elevate computer-assisted creativity: Our ultimate goal is to create musical pieces by retrieving the right set of parameters associated to a target emotion. This paper contains the description of (i) variables associated to fractal music and emotions; (ii) the data gathering method to obtain the tuples relating input parameters and emotional responses; (iii) the rules that where discovered by using an algorithm LR-FIR. Even though similar experiments whose intention is to elucidate emotional responses from music have been reported, this study stands because a connection is appointed between fractal-generated music and emotional responses, all with the purpose of advancing in computer-assisted creativity.


Recommender systems, knowledge discovery, rules extraction, fractal music.

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