@Article{          panteli.ea2017-computational,
    author       = {Panteli, Maria and Benetos, Emmanouil and Dixon, Simon},
    year         = {2017},
    title        = {A computational study on outliers in world music},
    abstract     = {The comparative analysis of world music cultures has been
                   the focus of several ethnomusicological studies in the
                   last century. With the advances of Music Information
                   Retrieval and the increased accessibility of sound
                   archives, large-scale analysis of world music with
                   computational tools is today feasible. We investigate
                   music similarity in a corpus of 8200 recordings of folk
                   and traditional music from 137 countries around the world.
                   In particular, we aim to identify music recordings that
                   are most distinct compared to the rest of our corpus. We
                   refer to these recordings as ‘outliers'. We use signal
                   processing tools to extract music information from audio
                   recordings, data mining to quantify similarity and detect
                   outliers, and spatial statistics to account for
                   geographical correlation. Our findings suggest that
                   Botswana is the country with the most distinct recordings
                   in the corpus and China is the country with the most
                   distinct recordings when considering spatial correlation.
                   Our analysis includes a comparison of musical attributes
                   and styles that contribute to the ‘uniqueness' of the
                   music of each country.},
    doi          = {10.1371/journal.pone.0189399},
    isbn         = {1111111111},
    issn         = {19326203},
    journal      = {PLoS ONE},
    keywords     = {computational musicology},
    mendeley-tags= {computational musicology},
    number       = {12},
    pages        = {1--29},
    pmid         = {29253027},
    volume       = {12}
}

{"_id":"e6iFT7Ej4w8t3rQc5","bibbaseid":"panteli-benetos-dixon-acomputationalstudyonoutliersinworldmusic-2017","authorIDs":[],"author_short":["Panteli, M.","Benetos, E.","Dixon, S."],"bibdata":{"bibtype":"article","type":"article","author":[{"propositions":[],"lastnames":["Panteli"],"firstnames":["Maria"],"suffixes":[]},{"propositions":[],"lastnames":["Benetos"],"firstnames":["Emmanouil"],"suffixes":[]},{"propositions":[],"lastnames":["Dixon"],"firstnames":["Simon"],"suffixes":[]}],"year":"2017","title":"A computational study on outliers in world music","abstract":"The comparative analysis of world music cultures has been the focus of several ethnomusicological studies in the last century. With the advances of Music Information Retrieval and the increased accessibility of sound archives, large-scale analysis of world music with computational tools is today feasible. We investigate music similarity in a corpus of 8200 recordings of folk and traditional music from 137 countries around the world. In particular, we aim to identify music recordings that are most distinct compared to the rest of our corpus. We refer to these recordings as ‘outliers'. We use signal processing tools to extract music information from audio recordings, data mining to quantify similarity and detect outliers, and spatial statistics to account for geographical correlation. Our findings suggest that Botswana is the country with the most distinct recordings in the corpus and China is the country with the most distinct recordings when considering spatial correlation. Our analysis includes a comparison of musical attributes and styles that contribute to the ‘uniqueness' of the music of each country.","doi":"10.1371/journal.pone.0189399","isbn":"1111111111","issn":"19326203","journal":"PLoS ONE","keywords":"computational musicology","mendeley-tags":"computational musicology","number":"12","pages":"1–29","pmid":"29253027","volume":"12","bibtex":"@Article{ panteli.ea2017-computational,\n author = {Panteli, Maria and Benetos, Emmanouil and Dixon, Simon},\n year = {2017},\n title = {A computational study on outliers in world music},\n abstract = {The comparative analysis of world music cultures has been\n the focus of several ethnomusicological studies in the\n last century. With the advances of Music Information\n Retrieval and the increased accessibility of sound\n archives, large-scale analysis of world music with\n computational tools is today feasible. We investigate\n music similarity in a corpus of 8200 recordings of folk\n and traditional music from 137 countries around the world.\n In particular, we aim to identify music recordings that\n are most distinct compared to the rest of our corpus. We\n refer to these recordings as ‘outliers'. We use signal\n processing tools to extract music information from audio\n recordings, data mining to quantify similarity and detect\n outliers, and spatial statistics to account for\n geographical correlation. Our findings suggest that\n Botswana is the country with the most distinct recordings\n in the corpus and China is the country with the most\n distinct recordings when considering spatial correlation.\n Our analysis includes a comparison of musical attributes\n and styles that contribute to the ‘uniqueness' of the\n music of each country.},\n doi = {10.1371/journal.pone.0189399},\n isbn = {1111111111},\n issn = {19326203},\n journal = {PLoS ONE},\n keywords = {computational musicology},\n mendeley-tags= {computational musicology},\n number = {12},\n pages = {1--29},\n pmid = {29253027},\n volume = {12}\n}\n\n","author_short":["Panteli, M.","Benetos, E.","Dixon, S."],"key":"panteli.ea2017-computational","id":"panteli.ea2017-computational","bibbaseid":"panteli-benetos-dixon-acomputationalstudyonoutliersinworldmusic-2017","role":"author","urls":{},"keyword":["computational musicology"],"metadata":{"authorlinks":{}},"downloads":0},"bibtype":"article","biburl":"https://hmb.sampaio.me/bibliografia.bib.txt","creationDate":"2020-09-17T19:50:05.163Z","downloads":0,"keywords":["computational musicology"],"search_terms":["computational","study","outliers","world","music","panteli","benetos","dixon"],"title":"A computational study on outliers in world music","year":2017,"dataSources":["n6MFY2CscQLDpJ7nT","RFLDZw5KyJdadDXDm"]}