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dc.contributor.authorHeydarian, Peymanen_NZ
dc.contributor.authorBainbridge, Daviden_NZ
dc.coverage.spatialThe Hague, Netherlandsen_NZ
dc.date.accessioned2020-02-17T19:40:01Z
dc.date.available2019en_NZ
dc.date.available2020-02-17T19:40:01Z
dc.date.issued2019en_NZ
dc.identifier.citationHeydarian, P., & Bainbridge, D. (2019). Dastgàh recognition in Iranian music: different features and optimized parameters. In Proceedings of 6th International Conference on Digital Libraries for Musicology (DLfM ’19) (pp. 53–57). New York, NY, USA: ACM Press. https://doi.org/10.1145/3358664.3361873en
dc.identifier.isbn9781450372398en_NZ
dc.identifier.urihttps://hdl.handle.net/10289/13439
dc.description.abstractIn this paper we report on the results of utilizing computational analysis to determine the dastgàh, the mode of music in the Iranian classical art music, using spectrogram and chroma features. We contrast the effectiveness of classifying music using the Manhattan distance and Gaussian Mixture Models (GMM). For our database of Iranian instrumental music played on a santur, using spectrogram and chroma features , we achieved accuracy rates of 90.11% and 80.2% when using Manhattan distance respectively. When using GMM with chroma, the accuracy rate was 89.0%. The effects of altering key parameters were also investigated, varying the amount of the training data and silence, as well as high frequency suppression on the results. The results from this phase of experimentation indicated that a 24 equal temperament was the best tone resolution. While experiments focused on dastgàh, with only minor adjustments the described techniques are applicable to traditional Persian, Kurdish, Turkish, Arabic and Greek music, and therefore suitable to use as a basis for a musicological tool that provides a broader form of cross-cultural audio search.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherACM Pressen_NZ
dc.rightsThis is the author's accepted version. The final publication is available at ACM via dx.doi.org/10.1145/3358664.3361873. © ACM.
dc.subjectcomputer scienceen_NZ
dc.subjectDastgàh recognitionen_NZ
dc.subjectPersian modeen_NZ
dc.subjectMaqàmen_NZ
dc.subjectChromaen_NZ
dc.subjectDSPen_NZ
dc.subjectcomputational musicologyen_NZ
dc.titleDastgàh recognition in Iranian music: different features and optimized parametersen_NZ
dc.typeConference Contribution
dc.identifier.doi10.1145/3358664.3361873en_NZ
dc.relation.isPartOfProceedings of 6th International Conference on Digital Libraries for Musicology (DLfM '19)en_NZ
pubs.begin-page53
pubs.elements-id249469
pubs.end-page57
pubs.finish-date2019-11-09en_NZ
pubs.place-of-publicationNew York, NY, USA
pubs.publication-statusPublisheden_NZ
pubs.start-date2019-11-09en_NZ


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