{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/104731"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/104731","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Experiments with the Shazam music identification algorithm","abstract":"The motivation of this study is to identify music without the original recording. The existing solutions tackle variations in some properties such as background sound and white noise, but the identification of samples containing large variations in key, tempo, ornamentation, and harmonization remains largely unsolved. This study takes an existing algorithm and uses an existing data set to explore the parameters required for successful identification, as well as variations in key. The findings show a simple way to identify and normalize the key of a sample. 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