A Data Mining Approach for Taal and Laya Recognition of North Indian Classical Music

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dc.contributor.authorHettiarachchi, B.
dc.contributor.authorCharles, J.
dc.contributor.authorLekamge, L.S.
dc.date.accessioned2021-02-02T04:28:45Z
dc.date.available2021-02-02T04:28:45Z
dc.date.issued2020
dc.description.abstractMusic plays a vital role in our day-to-day life, especially in today’s digital age. Computational musicology is an interdisciplinary area in which computational methods are used to analyse musical structures: notes, chords, rhythms, and patterns thereof. While western classical music is extensively explored, North Indian classical music remains to be explored computationally. Meanwhile, our recent review of the literature revealed that Raag identification is among the frequent data mining tasks applied to North Indian music. However, recognition of their rhythmic structures is also important as it serves in a multitude of applications e.g., intelligent music archival, enhanced navigation and retrieval of music, and informed music listening. Rhythm in North Indian classical music revolves around the theme of Taal - the cycle of beats of specific syllables and beats. It is the most basic information for listeners to follow the rhythmic structure of music. Laya is the speed of Taal and may vary between Vilambit (slow), Madhya (medium), and Drut (fast). Taken together, the main aim of the proposed study is to apply data mining for the recognition of Taal and Laya in North Indian classical music. A dataset of 151 excerpts (2mins; 44.1 kHz; stereo; .wav) from CompMusic Hindustani test corpus, belonging to four popular Taals is used in the study. For each Taal, there are excerpts in three Layas. Acoustic features pertaining to fluctuation, beat spectrum, onsets, event density, tempo, metre, metroid, and pulse clarity will be extracted using MATLAB MIRToolbox. The performance of frequently adopted algorithms e.g., k-Nearest Neighbor and Support Vector Machine is to be compared in the study with the aim of developing a classifier with higher accuracy. Even though the findings of the study would be limited by the consideration of a smaller dataset, the study would make a promising contribution through computationally exploring rhythmic patterns of a great musical tradition Keywords: Music data mining, Taal and Laya recognition, North Indian classical music, Rhythmic analysis, Computational musicologyen_US
dc.identifier.isbn9789550481293
dc.identifier.urihttp://www.erepo.lib.uwu.ac.lk/bitstream/handle/123456789/5731/proceeding_oct_08-208.pdf?sequence=1&isAllowed=y
dc.language.isoenen_US
dc.publisherUva Wellassa University of Sri Lankaen_US
dc.relation.ispartofseries;International Research Conference
dc.subjectMusicen_US
dc.subjectComputer Scienceen_US
dc.subjectInformation Scienceen_US
dc.titleA Data Mining Approach for Taal and Laya Recognition of North Indian Classical Musicen_US
dc.title.alternativeInternational Research Conference 2020en_US
dc.typeOtheren_US
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