Umjetna inteligencija u glazbenoj produkciji

master's thesis

• Title (english): Artificial intelligence in music production
• Author: Stefan Lončar
• Mentor: Ivan Dunđer (mentor)
• Committee member: Vjera Lopina (član povjerenstva)
• Committee member: Sanja Seljan (predsjednik povjerenstva)
• Committee member: Ivan Dunđer (član povjerenstva)
• Granter: University of Zagreb; Faculty of Humanities and Social Sciences; (Department of information and Communication sciences); Zagreb
• Defense date and country: 2024-02-05, Croatia
• Scientific / art field, discipline and subdiscipline: SOCIAL SCIENCES; Information and Communication Sciences; Organization and Informatics

Abstract

Glazbena produkcija se kroz povijest uvijek razvijala u korak s tehnologijom. Od stvaranja notnih zapisa kao simboličke reprezentacije glazbe koja će biti izvođena, preko tehnologija snimanja u glazbenim studijima i pojave DAW sustava, do današnjeg automatskog generiranja muzičkog sadržaja za koje su u konačnici zaslužni algoritmi strojnog učenja. Osnova istraživanja primjene umjetne inteligencije u glazbenoj produkciji je smanjenje troškova i uključivanje te olakšavanje procesa vezanih u stvaranje audio sadržaja. Iako je primjena algoritama dubokog učenja u procesima kreiranja glazbenog sadržaja tek na svojim počecima, već sada je jasno koliko će utjecati na automatizaciju procesa unutar cijele glazbene industrije.

Abstract (english)

Throughout its history, music production has always developed in step with technology. From the creation of musical notation as a symbolic representation of the music that will be performed, through recording technologies in music studios and the emergence of DAW systems, to today’s automatic generation of musical content, which is ultimately due to machine and deep learning algorithms. The basis of research into the application of artificial intelligence in music production is the reduction of costs and the inclusion and facilitation of processes related to the creation of audio content. Although the application of deep learning algorithms in the processes of creating music content is only at its beginning, it is already clear how much it will affect the automation of processes within the entire music industry.

• Keywords: glazbena produkcija; glazbeni producent; glazbena industrija; strojno učenje; duboko učenje; umjetna inteligencija; inteligentna muzička produkcija; računalno stvaranje glazbe; računalno generiranje glazbe
• Keywords (english): music production; music producer; music industry; machine learning; deep learning; artificial intelligence; intelligent music production; computer music creation; computer music generation
• Language: croatian
• URN:NBN: urn:nbn:hr:131:469564
• Study programme: Title: Information Sciences; specializations in: Archivistics Study, Library Science, Information Sciences (research), Information Sciences (teaching), Museology and heritage management, Informatology; Course: Information Sciences (research); Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra informacijskih znanosti (magistar/magistra informacijskih znanosti)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Access restricted to students and staff of home institution
• Created on: 2024-02-06 19:20:45