Combining Audio Fingerprints
Large music collections are now more common than ever before. Yet, search technology for music is still in its infancy. Audio fingerprinting is one method that allows searching for music. In this thesis several audio fingerprinting solutions are combined into a single solution to determine if such...
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Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap
2008
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ndltd-UPSALLA1-oai-DiVA.org-ntnu-88692013-01-08T13:26:25ZCombining Audio FingerprintsengLarsen, Vegard AndreasNorges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskapInstitutt for datateknikk og informasjonsvitenskap2008ntnudaimSIF2 datateknikkData- og informasjonsforvaltningLarge music collections are now more common than ever before. Yet, search technology for music is still in its infancy. Audio fingerprinting is one method that allows searching for music. In this thesis several audio fingerprinting solutions are combined into a single solution to determine if such a combination can yield better results than any of the solutions can separately. The solution is used to find duplicate music files in a personal collection. The results show that applying the weighted root-mean square (WRMS) to the problem most effectively ranked the results in a satisfying manner. It was notably better than the other approaches tried. The WRMS produced 61% more correct matches than the original FDMF solution, and 49% more correct matches than libFooID. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8869Local ntnudaim:4014application/pdfinfo:eu-repo/semantics/openAccess |
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English |
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Others
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ntnudaim SIF2 datateknikk Data- og informasjonsforvaltning |
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ntnudaim SIF2 datateknikk Data- og informasjonsforvaltning Larsen, Vegard Andreas Combining Audio Fingerprints |
description |
Large music collections are now more common than ever before. Yet, search technology for music is still in its infancy. Audio fingerprinting is one method that allows searching for music. In this thesis several audio fingerprinting solutions are combined into a single solution to determine if such a combination can yield better results than any of the solutions can separately. The solution is used to find duplicate music files in a personal collection. The results show that applying the weighted root-mean square (WRMS) to the problem most effectively ranked the results in a satisfying manner. It was notably better than the other approaches tried. The WRMS produced 61% more correct matches than the original FDMF solution, and 49% more correct matches than libFooID. |
author |
Larsen, Vegard Andreas |
author_facet |
Larsen, Vegard Andreas |
author_sort |
Larsen, Vegard Andreas |
title |
Combining Audio Fingerprints |
title_short |
Combining Audio Fingerprints |
title_full |
Combining Audio Fingerprints |
title_fullStr |
Combining Audio Fingerprints |
title_full_unstemmed |
Combining Audio Fingerprints |
title_sort |
combining audio fingerprints |
publisher |
Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap |
publishDate |
2008 |
url |
http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8869 |
work_keys_str_mv |
AT larsenvegardandreas combiningaudiofingerprints |
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