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Discovering structural similarities among rāgas in Indian Art Music: a computational approach
Indian Art Music has a huge variety of rāgas . The similarity across rāgas has traditionally been approached from various musicological viewpoints. This work aims at discovering structural similarities among renditions of rāgas using a data-driven approach. Starting from melodic contours, we obtain...
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Published in: | Sadhana (Bangalore) 2019-05, Vol.44 (5), p.1-20, Article 120 |
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description | Indian Art Music has a huge variety of
rāgas
. The similarity across
rāgas
has traditionally been approached from various musicological viewpoints. This work aims at discovering structural similarities among renditions of
rāgas
using a data-driven approach. Starting from melodic contours, we obtain the descriptive note-level transcription of each rendition. Repetitive note patterns of variable and fixed lengths are derived using stochastic models. We propose a latent variable approach for raga distinction based on statistics of these patterns. The posterior probability of the latent variable is shown to capture similarities across raga renditions. We show that it is possible to visualize the similarities in a low-dimensional embedded space. Experiments show that it is possible to compare and contrast relations and distances between ragas in the embedded space with the musicological knowledge of the same for both Hindustani and Carnatic music forms. The proposed approach also shows robustness to duration of rendition. |
doi_str_mv | 10.1007/s12046-019-1112-2 |
format | article |
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rāgas
. The similarity across
rāgas
has traditionally been approached from various musicological viewpoints. This work aims at discovering structural similarities among renditions of
rāgas
using a data-driven approach. Starting from melodic contours, we obtain the descriptive note-level transcription of each rendition. Repetitive note patterns of variable and fixed lengths are derived using stochastic models. We propose a latent variable approach for raga distinction based on statistics of these patterns. The posterior probability of the latent variable is shown to capture similarities across raga renditions. We show that it is possible to visualize the similarities in a low-dimensional embedded space. Experiments show that it is possible to compare and contrast relations and distances between ragas in the embedded space with the musicological knowledge of the same for both Hindustani and Carnatic music forms. The proposed approach also shows robustness to duration of rendition.</description><identifier>ISSN: 0256-2499</identifier><identifier>EISSN: 0973-7677</identifier><identifier>DOI: 10.1007/s12046-019-1112-2</identifier><language>eng</language><publisher>New Delhi: Springer India</publisher><subject>Analogies ; Conditional probability ; Engineering ; Monte Carlo simulation</subject><ispartof>Sadhana (Bangalore), 2019-05, Vol.44 (5), p.1-20, Article 120</ispartof><rights>Indian Academy of Sciences 2019</rights><rights>Copyright Springer Nature B.V. 2019</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2742-a1b5f26caeb706681a41a7f485164ed1e9b1259129ca0bc9bb85055bf3d6e5103</citedby><cites>FETCH-LOGICAL-c2742-a1b5f26caeb706681a41a7f485164ed1e9b1259129ca0bc9bb85055bf3d6e5103</cites><orcidid>0000-0002-4202-2967</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids></links><search><creatorcontrib>Ranjani, H G</creatorcontrib><creatorcontrib>Paramashivan, Deepak</creatorcontrib><creatorcontrib>Sreenivas, Thippur V</creatorcontrib><title>Discovering structural similarities among rāgas in Indian Art Music: a computational approach</title><title>Sadhana (Bangalore)</title><addtitle>Sādhanā</addtitle><description>Indian Art Music has a huge variety of
rāgas
. The similarity across
rāgas
has traditionally been approached from various musicological viewpoints. This work aims at discovering structural similarities among renditions of
rāgas
using a data-driven approach. Starting from melodic contours, we obtain the descriptive note-level transcription of each rendition. Repetitive note patterns of variable and fixed lengths are derived using stochastic models. We propose a latent variable approach for raga distinction based on statistics of these patterns. The posterior probability of the latent variable is shown to capture similarities across raga renditions. We show that it is possible to visualize the similarities in a low-dimensional embedded space. Experiments show that it is possible to compare and contrast relations and distances between ragas in the embedded space with the musicological knowledge of the same for both Hindustani and Carnatic music forms. The proposed approach also shows robustness to duration of rendition.</description><subject>Analogies</subject><subject>Conditional probability</subject><subject>Engineering</subject><subject>Monte Carlo simulation</subject><issn>0256-2499</issn><issn>0973-7677</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNp1kE1LAzEQhoMoWKs_wFvAczST3SS73kr9KlS86NUwm2ZrSvfDZFfw6H_zh5lSwZOnGZj3mRkeQs6BXwLn-iqC4LliHEoGAIKJAzLhpc6YVlofpl5IxURelsfkJMYN50LzIpuQ1xsfbffhgm_XNA5htMMYcEujb_wWgx-8ixSbLk3D99caI_UtXbQrjy2dhYE-jtHba4rUdk0_Djj4rk049n3o0L6dkqMat9Gd_dYpebm7fZ4_sOXT_WI-WzIrdC4YQiVroSy6SnOlCsAcUNd5IUHlbgWurEDIEkRpkVe2rKpCcimrOlspJ4FnU3Kx35vOvo8uDmbTjSF9Eo0QAFprLnVKwT5lQxdjcLXpg28wfBrgZqfR7DWapNHsNBqRGLFnYr9z5MLf5v-hH0IBdf4</recordid><startdate>20190501</startdate><enddate>20190501</enddate><creator>Ranjani, H G</creator><creator>Paramashivan, Deepak</creator><creator>Sreenivas, Thippur V</creator><general>Springer India</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0002-4202-2967</orcidid></search><sort><creationdate>20190501</creationdate><title>Discovering structural similarities among rāgas in Indian Art Music: a computational approach</title><author>Ranjani, H G ; Paramashivan, Deepak ; Sreenivas, Thippur V</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2742-a1b5f26caeb706681a41a7f485164ed1e9b1259129ca0bc9bb85055bf3d6e5103</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Analogies</topic><topic>Conditional probability</topic><topic>Engineering</topic><topic>Monte Carlo simulation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ranjani, H G</creatorcontrib><creatorcontrib>Paramashivan, Deepak</creatorcontrib><creatorcontrib>Sreenivas, Thippur V</creatorcontrib><collection>CrossRef</collection><jtitle>Sadhana (Bangalore)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ranjani, H G</au><au>Paramashivan, Deepak</au><au>Sreenivas, Thippur V</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Discovering structural similarities among rāgas in Indian Art Music: a computational approach</atitle><jtitle>Sadhana (Bangalore)</jtitle><stitle>Sādhanā</stitle><date>2019-05-01</date><risdate>2019</risdate><volume>44</volume><issue>5</issue><spage>1</spage><epage>20</epage><pages>1-20</pages><artnum>120</artnum><issn>0256-2499</issn><eissn>0973-7677</eissn><abstract>Indian Art Music has a huge variety of
rāgas
. The similarity across
rāgas
has traditionally been approached from various musicological viewpoints. This work aims at discovering structural similarities among renditions of
rāgas
using a data-driven approach. Starting from melodic contours, we obtain the descriptive note-level transcription of each rendition. Repetitive note patterns of variable and fixed lengths are derived using stochastic models. We propose a latent variable approach for raga distinction based on statistics of these patterns. The posterior probability of the latent variable is shown to capture similarities across raga renditions. We show that it is possible to visualize the similarities in a low-dimensional embedded space. Experiments show that it is possible to compare and contrast relations and distances between ragas in the embedded space with the musicological knowledge of the same for both Hindustani and Carnatic music forms. The proposed approach also shows robustness to duration of rendition.</abstract><cop>New Delhi</cop><pub>Springer India</pub><doi>10.1007/s12046-019-1112-2</doi><tpages>20</tpages><orcidid>https://orcid.org/0000-0002-4202-2967</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Analogies Conditional probability Engineering Monte Carlo simulation |
title | Discovering structural similarities among rāgas in Indian Art Music: a computational approach |
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