20.500.12556/RUL-131009 SymCHM—an unsupervised approach for pattern discovery in symbolic music with a compositional hierarchical model This paper presents a compositional hierarchical model for pattern discovery in symbolic music. The model can be regarded as a deep architecture with a transparent structure. It can learn a set of repeated patterns within individual works or larger corpora in an unsupervised manner, relying on statistics of pattern occurrences, and robustly infer the learned patterns in new, unknown works. A learned model contains representations of patterns on different layers, from the simple short structures on lower layers to the longer and more complex music structures on higher layers. A pattern selection procedure can be used to extract the most frequent patterns from the model. We evaluate the model on the publicly available JKU Patterns Datasets and compare the results to other approaches. music information retrieval compositional modelling pattern discovery symbolic music representations pridobivanje informacij iz glasbe kompozicionalno modeliranje odkrivanje vzorcev simbolne predstavitve glasbe true false true Angleški jezik Slovenski jezik Članek v reviji 2021-09-21 12:15:24 2021-09-21 12:15:25 2022-09-10 04:09:21 0000-00-00 00:00:00 2017 0 0 20 str. iss. 11, art. 1135 Vol. 7 2017 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004:78 2076-3417 10.3390/app7111135 1537631683 RAZ_Pesek_Matevz_2017.pdf RAZ_Pesek_Matevz_2017.pdf 1 97589F1A41E0E9BF66FA78D99818EC2A 7a0647edecbf35245bcfc10cee2f4f4344c26d7e0157cb5e13436fd6884e1f22 c53b59af-1ac4-11ec-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=148235 http://www.mdpi.com/2076-3417/7/11/1135 1 9221b658-1ac4-11ec-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=148234 Fakulteta za računalništvo in informatiko 0 0 0