An evaluation of musical pattern discovery algorithms using a visualisation application

Show simple item record

dc.contributor Helsingin yliopisto, Matemaattis-luonnontieteellinen tiedekunta fi
dc.contributor University of Helsinki, Faculty of Science en
dc.contributor Helsingfors universitet, Matematisk-naturvetenskapliga fakulteten sv
dc.contributor.author Wargelin, Matias
dc.date.issued 2021
dc.identifier.uri URN:NBN:fi:hulib-202108313580
dc.identifier.uri http://hdl.handle.net/10138/333845
dc.description.abstract Musical pattern discovery refers to the automated discovery of important repeated patterns, such as melodies and themes, from music data. Several algorithms have been developed to solve this problem, but evaluating the algorithms has been difficult without proper visualisations of the output of the algorithms. To address this issue a web application named Mupadie was built. Mupadie accepts MIDI music files as input and visualises the outputs of musical pattern discovery algorithms, with implementations of SIATEC and TTWIA built in the application. Other algorithms can be visualised if the algorithm output is uploaded to Mupadie as a JSON file that follows a specified data structure. Using Mupadie, an evaluation of SIATEC and TTWIA was conducted. Mupadie was found to be a useful tool in the qualitative evaluation of these musical pattern discovery algorithms; it helped reveal systematically recurring issues with the discovered patterns, some previously known and some previously undocumented. The findings were then used to suggest improvements to the algorithms. en
dc.language.iso eng
dc.publisher Helsingin yliopisto fi
dc.publisher University of Helsinki en
dc.publisher Helsingfors universitet sv
dc.subject musical pattern discovery
dc.subject music information retrieval
dc.subject web application
dc.title An evaluation of musical pattern discovery algorithms using a visualisation application en
dc.title.alternative Visualisointisovelluksen avulla tehty arviointi musiikillisia kuvioita löytävistä algoritmeista fi
dc.type.ontasot pro gradu -tutkielmat fi
dc.type.ontasot master's thesis en
dc.type.ontasot pro gradu-avhandlingar sv
dct.identifier.urn URN:NBN:fi:hulib-202108313580
dc.subject.specialization Algoritmit fi
dc.subject.specialization Algorithms en
dc.subject.specialization Algoritmer sv
dc.subject.degreeprogram Tietojenkäsittelytieteen maisteriohjelma fi
dc.subject.degreeprogram Master's Programme in Computer Science en
dc.subject.degreeprogram Magisterprogrammet i datavetenskap sv

Files in this item

Total number of downloads: Loading...

Files Size Format View
Wargelin_Matias_maisterintutkielma_2021.pdf 1.475Mb PDF View/Open

This item appears in the following Collection(s)

Show simple item record