20.500.12556/RUL-132221 Algorithmic music for therapy effectiveness and perspectives This study assessed the short-term effects of conventional (i.e., human-composed) and algorithmic music on the relaxation level. It also investigated whether algorithmic compositions are perceived as music and are distinguishable from human-composed music. Three hundred twenty healthy volunteers were recruited and randomly allocated to two groups where they listened to either their preferred music or algorithmic music. Another 179 healthy subjects were allocated to four listening groups that respectively listened to: music composed and performed by a human, music composed by a human and performed by a machine; music composed by a machine and performed by a human, music composed and performed by a machine. In the first experiment, participants underwent one of the two music listening conditions-preferred or algorithmic music' in a comfortable state. In the second one, participants were asked to evaluate, through an online questionnaire, the musical excerpts they listened to. The Visual Analogue Scale was used to evaluate their relaxation levels before and after the music listening experience. Other outcomes were evaluated through the responses to the questionnaire. The relaxation level obtained with the music created by the algorithms is comparable to the one achieved with preferred music. Statistical analysis shows that the relaxation level is not affected by the composer, the performer, or the existence of musical training. On the other hand, the perceived effect is related to the performer. Finally, music composed by an algorithm and performed by a human is not distinguishable from that composed by a human. algorithmic music human/machine composition Melomics-Health relaxation therapeutic music listening true false true Angleški jezik Angleški jezik Članek v reviji 2021-10-18 11:40:57 2021-10-18 11:57:17 2022-09-12 04:11:29 0000-00-00 00:00:00 2021 0 0 13 str. iss. 19 (art. 8833) Vol. 11 2021 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004 2076-3417 10.3390/app11198833 78036739 RAZ_Raglio_Alfredo_2021.pdf RAZ_Raglio_Alfredo_2021.pdf 1 AEC959729EF39AA1DA86555C3E07B9E4 4abdef6374e7c21457ebe5f7a21e55a8465900583680cb1f7301e9bfceeeed42 376772a6-2ff8-11ec-abdb-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=149770 https://www.mdpi.com/2076-3417/11/19/8833 0 3f401319-2ff8-11ec-abdb-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=149771 Ekonomska fakulteta 0 0 0