a b s t r a c tIn this research, a system is built that generates bagana music, a traditional lyre from Ethiopia, based on a first order Markov model. Due to the size of many datasets it is often only possible to get rich and reliable statistics for low order models, yet these do not handle structure very well and their output is often very repetitive. A first contribution of this paper is to propose a method that allows the enforcement of structure and repetition within music, thus handling long term coherence with a first order model. The second goal of this research is to explain and propose different ways in which low order Markov models can be used to build quality assessment metrics for an optimization algorithm. These are then implemented in a variable neighborhood search algorithm that generates bagana music. The results are examined and thoroughly evaluated.
This paper develops and applies sequential pattern mining to a corpus of songs for the bagana, a large lyre played in Ethiopia. An important aspect of this repertoire is the unique availability of rare motifs that have been used by a master bagana teacher in Ethiopia. The method is applied to find antipatterns: patterns that are surprisingly rare in a corpus of bagana songs. In contrast to previous work, this is performed without an explicit set of background pieces. The results of this study show that data mining methods can reveal with high significance these antipatterns of interest based on the computational analysis of a small corpus of bagana songs.
La revue scientifique électronique pour les recherches sur Bruxelles / Het elektronisch wetenschappelijk tijdschrift voor onderzoek over Brussel / The e-journal for academic research on Brussels Collection générale | 2015 Les musiciens gnawa à Bruxelles : une reconfiguration culturelle Gnawa-muzikanten in Brussel: een culturele herconfiguratie The Gnawa musicians in Brussels: a cultural reorganisation
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