Culture-aware approaches to modeling and description of intonation using multimodal data

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• dc.contributor.author Koduri, Gopala Krishnaca
• dc.date.accessioned 2018-07-02T08:53:51Z
• dc.date.available 2018-07-02T08:53:51Z
• dc.date.issued 2014
• dc.description Comunicació presentada a la International Conference on Knowledge Engineering and Knowledge Management (EKAW), que es va celebrar del 24 al 28 de novembre de 2014 a Linkoping, Suècia.
• dc.description.abstract Computational approaches that conform to the cultural context are of paramount importance in music information research. The current state-of-the-art has a limited view of such context, which manifests in our ontologies, data-, cognition- and interaction-models that are biased to the market-driven popular music. In a step towards addressing this, the thesis draws upon multimodal data sources concerning art music traditions, extracting culturally relevant and musically meaningful information about melodic intervals from each of them and structuring it with formal knowledge representations. As part of this, we propose novel approaches to describe intonation in audio music recordings and to use and adapt the semantic web infrastructure to complement this with the knowledge extracted from text data. Due to the complementary nature of the data sources, structuring and linking the extracted information results in a symbiosis mutually enriching their information. Over this multimodal knowledge base, we propose similarity measures for the discovery of musical entities, yielding a culturally-sound navigation space.en
• dc.description.sponsorship This thesis is supervised by Dr. Xavier Serra, and was partly funded by the European Research Council under the European Union’s Seventh Framework Program, as part of the CompMusic project (ERC grant agreement 267583).
• dc.format.mimetype application/pdf
• dc.identifier.citation Koduri GK. Culture-aware approaches to modeling and description of intonation using multimodal data. In: Lambrix P. et al, editors. Knowledge Engineering and Knowledge Management. EKAW 2014; 2014 Nov 24-28; Linkoping, Sweden. Berlin: Springer; 2015. p. 209-17. (Lecture Notes in Computer Science, 8289). DOI: 10.1007/978-3-319-17966-7_30
• dc.identifier.doi http://dx.doi.org/10.1007/978-3-319-17966-7_30
• dc.identifier.uri http://hdl.handle.net/10230/35013
• dc.language.iso eng
• dc.publisher Springerca
• dc.relation.ispartof Lambrix P. et al, editors. Knowledge Engineering and Knowledge Management. EKAW 2014; 2014 Nov 24-28; Linkoping, Sweden. Berlin: Springer; 2015. p. 209-17.
• dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/267583
• dc.rights © Springer The final publication is available at Springer via https://link.springer.com/chapter/10.1007/978-3-319-17966-7_30
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.subject.keyword Music information retrievalen
• dc.subject.keyword Music recommendationen
• dc.subject.keyword Music traditionen
• dc.title Culture-aware approaches to modeling and description of intonation using multimodal dataca
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/acceptedVersion