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Iskanje notnih vzorcev v slovenskem samospevu med obema vojnama: Kogoj, Osterc, Škerjanc
ID Borsan, Vanessa Nina (Author), ID Stefanija, Leon (Mentor) More about this mentor... This link opens in a new window, ID Pesek, Matevž (Co-mentor)

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Abstract
Magistrsko delo se ukvarja z vprašanjem vzorcev v slovenskem medvojnem samospevu. Raziskava vključuje 83 skladb treh ključnih skladateljev takratnega časa – Marija Kogoja (1892–1956), Lucijana Marijo Škerjanca in Slavka Osterca (1895–1941). Sprva je orisano glasbeno-zgodovinsko ozadje žanra in vseh treh avtorjev, ki pripomore k lažjeum razumevanju rezultatov. Temu sledi računalniška glasbena analiza zastavljenega korpusa. Prva ustvarjena računalniška koda, pisana v jeziku Python (z uporabo music21), ki se ukvarja z (meta)podatkovnimi bazami celotnega korpusa, korpusa posameznih skladateljev ter s posameznimi skladbami. Analiza pri tem upošteva šestnajst različnih parametrov. V nadaljevanju besedilo z metodo iskanja n-gramov obravnava melodične in tri različne ritmične vzorce. Po splošnem pregledu vzorcev se osredotoči na petnajst notnih primerov. Nabor samospevov je izbran tako, da tudi v svoji okrnjenosti izrišejo določene poteze vsakega izmed skladateljev. Na koncu so podani vsebinska sinteza, ovrednotenje računalniškega modela in predlogi za nadaljnje raziskovanje.

Language:Slovenian
Keywords:slovenski samospev, digitalna muzikologija, n-grami, notni vzorci, Python
Work type:Master's thesis/paper
Organization:FF - Faculty of Arts
Year:2020
PID:20.500.12556/RUL-121664 This link opens in a new window
Publication date in RUL:22.10.2020
Views:703
Downloads:186
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Secondary language

Language:English
Title:Discovering Patterns in Slovene Lied In-between the World Wars: Kogoj, Osterc, Škerjanc
Abstract:
Centred topic of my master’s thesis is music patterns in Slovenian lied in-between the two World wars. The research sets its fundamental focus to three central composers of the time – Marij Kogoj (1892–1956), Lucijan Marija Škerjanc (1900–1973) and Slavko Osterc (1895–1941). Firstly, the thesis establishes musically-historical groundwork which mainly serves as a mediator between the gathered results and their interpretation. This is followed by a digital analysis of music notation which consists of two preeminent frames, both executed in Python language with music21. First model carries out corpus (meta)data processing through sixteen different parameters. N-gram analysis method establishes the second model. It returns series of melody patterns (music intervals) and three different types of rhythmic patterns. Both are commented separately and then compared. This method includes a selection of five music pieces per author. The thesis concludes its findings with content synthesis, evaluation of established computational model and encourages further research within the observed topic.

Keywords:Slovene lied, digital musicology, n-grams, music patterns, Python

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