ПОВЕЌЕГЛАСНАТА МАКЕДОНСКА СЕЛСКА ТРАДИЦИЈА НИЗ ДИГИТАЛНИОТ ДИСКУРС (Состојби и перспективи на истражувањето)

The present methods of ethnomusicological analysis indicate a partial study of musical-folk examples, and conclusions on general regularities are made in the final stages of the research. Digital databases of the described data could significantly economize this long and complex process, even partia...

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Veröffentlicht in:Spektar (Skopje, Macedonia) Macedonia), 2023 (82), p.183-197
1. Verfasser: Kostic Markovic, Branka
Format: Artikel
Sprache:mac
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Zusammenfassung:The present methods of ethnomusicological analysis indicate a partial study of musical-folk examples, and conclusions on general regularities are made in the final stages of the research. Digital databases of the described data could significantly economize this long and complex process, even partially automate it, and definitely make it much shorter and more efficient. The digital databases already sort and classify data by groups based on preset parameters when you enter it. With that, the ethnomusicological science will also change, because it will not operate with individual examples, but with already classified and categorized groups, which will allow a deeper understanding of the music itself and its genesis. Let us remember the words from the very beginning of this document that Macedonian folk songs, as a specific part of folk creativity, are a widely known artistic work. From an ethnomusicological viewpoint, that art work was created as an inseparable union of the song (music) and the poetic text. The digital discourse can only simplify it, make them more efficient, and finally result in a significantly more precise version of the previously mostly verbal descriptive analytical procedures. In the near future this would enable a deeper penetration into the essence of the folk song, and thus, through its better understanding will also lead to an essential knowledge of the creative processes that lead to its creation. The time to record new works is slowing down, but the time for deeper and content-based analyses is still ahead, thanks to the processing of digitized data.
ISSN:0352-2423