Statistical rules in constraint-based programming
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In this paper we introduce a system that first generates statistical analysis data from a musical score. The results are then translated automatically to constraint rules that in turn can be used in com- bination with ordinary rules to generate scores that have similar statistical distributions than the original. Statistical analysis rules are formalized using our special rule syntax where our focus will be in the pattern-matching part of the rules. The pattern-matching part has two important tasks in our paper: first, it is used to extract various musical entities from the score, such as melodic, harmonic and voice-leading formations; second, it is used also to generate statistical rules which will be used in the re-synthesis part of our system. We first introduce the rule syntax. After this we discuss a practical case study where we analyze a melodic line. Finally we generate out of this material statistical rules which are used to produce new scores.