A Mono-objective Evolutionary Model for Affective Algorithmic Composition

The study of Affective Music Composition indicates that musical features can associate with emotions. Thus, Affective Algorithmic Composition systems implement such features to generate melodies that can express or induce emotions. These systems apply to different fields, like health and entertainment. However, the composition of melodies with unlimited duration time and diversity is still an open question. This work aims to identify strategies to perform many affective transformations in melodies. This work presents emotional models, the most implemented musical features in the literature, and an evolutionary mono-objective model for an affective transformative system.