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Poravnava zvočnih in notnih zapisov ljudske glasbe
ID Kralj, Samo (Author), ID Marolt, Matija (Mentor) More about this mentor... This link opens in a new window

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PID: 20.500.12556/rul/e1ab5264-ba1a-4052-8e16-3a2020205bb0

Abstract
V magistrski nalogi obravnavamo problem poravnave zvočnih in notnih zapisov za ljudsko glasbo. Za cilj si zadamo prilagoditi standardne metode za poravnavo zvočnih in notnih zapisov za uporabo na arhivu ljudske glasbe. Algoritme za poravnavo zvočnih in notnih zapisov nato uporabimo za iskanje v arhivu ljudske glasbe. Pri ljudski glasbi se pogosto srečamo s problemom slabše kakovosti petja pevcev, ki pogosto niso profesionalni pevci. Slabša kakovost zvočnih zapisov oteži iskanje po arhivu glasbe. V magistrski nalogi preizkusimo nekaj pristopov za izboljšanje učinkovitosti iskanja po arhivu ljudske glasbe. Pri načrtovanju rešitev upoštevamo lastnosti ljudske glasbe kot so specifična porazdelitev tonov pri ljudski glasbi. Naše rešitve preizkusimo na arhivu slovenske ljudske glasbe, kjer dosežemo pomembno izboljšanje rezultatov v primerjavi s standardnimi metodami.

Language:Slovenian
Keywords:ljudska glasba, poravnava glasbenih zapisov, poizvedba s petjem, dinamično časovno krivljenje, skriti model Markova
Work type:Master's thesis/paper
Organization:FRI - Faculty of Computer and Information Science
Year:2016
PID:20.500.12556/RUL-84524 This link opens in a new window
Publication date in RUL:29.08.2016
Views:1261
Downloads:419
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Secondary language

Language:English
Title:Audio to score alignment of folk music
Abstract:
The thesis deals with the problem of audio to score alignment of folk music. Our goal is to adapt standard methods for audio to score alignment for aligning folk music. Alignment algorithms are then used for querying music in folk music archives. In folk music, the quality of recordings is often poor, due to recording conditions, and because singers are often not professionals. This makes alignment with standard approaches difficult. In our master thesis we develop new approaches to improve alignment in folk music archives by exploiting the characteristics of folk music, such as its tone distribution. We test our algorithms on slovenian folk music and show that we achieve improvement over standard methods.

Keywords:folk music, music alignment, query by humming, dynamic time warping, hidden Markov model

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