Discovery of generalized interval patterns
نویسندگان
چکیده
This paper presents a method for pattern discovery based on viewpoints and feature set patterns. The representation for pattern components accommodates in a fully general way the taxonomic relationships that may exist between interval classes. A heuristic probabilistic hill climbing algorithm is developed to rapidly direct the search towards interesting patterns. The method can be used for single piece analysis, for comparison of two pieces, and also for pattern analysis of a large corpus. The method is applied to the music of French singer-songwriter Georges Brassens. Keywords— pattern discovery, melodic interval, viewpoints, feature set, subsumption.
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