20.500.12556/RUL-133130 An analysis of rhythmic patterns with unsupervised learning This paper presents a model capable of learning the rhythmic characteristics of a music signal through unsupervised learning. The model learns a multi-layer hierarchy of rhythmic patterns ranging from simple structures on lower layers to more complex patterns on higher layers. The learned hierarchy is fully transparent, which enables observation and explanation of the structure of the learned patterns. The model employs tempo-invariant encoding of patterns and can thus learn and perform inference on tempo-varying and noisy input data. We demonstrate the model’s capabilities of learning distinctive rhythmic structures of different music genres using unsupervised learning. To test its robustness, we show how the model can efficiently extract rhythmic structures in songs with changing time signatures and live recordings. Additionally, the model’s time-complexity is empirically tested to show its usability for analysis-related applications. music information retrieval rhythm analysis compositional hieararchical model pridobivanje informacij iz glasbe analiza ritma kompozicionalni hierarhični model true false true Angleški jezik Slovenski jezik Članek v reviji 2021-11-12 09:44:39 2021-11-12 09:44:39 2022-09-12 04:15:00 0000-00-00 00:00:00 2020 0 0 22 str. iss. 1, art. 178 Vol. 10 Jan. 2020 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004:78 2076-3417 10.3390/app10010178 1538490051 RAZ_Pesek_Matevz_2020.pdf RAZ_Pesek_Matevz_2020.pdf 1 761959FF39C823DFC661E056847F50D8 a806f634349c4524e6934c7279baf97f10275c095d8ebacae00702676243155c ea328b9c-4394-11ec-abdb-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=150947 https://www.mdpi.com/2076-3417/10/1/178 1 b65609d7-4394-11ec-abdb-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=150946 Fakulteta za računalništvo in informatiko 0 0 0