By mining user-generated text content we can obtain musicrelated/ninformation that could not otherwise be extracted/nfrom audio signals or symbolic score representations. In/nthis paper we propose a methodology for extracting/nmusic-related semantic information from an online/ndiscussion forum, rasikas.org, dedicated to the Carnatic/nmusic tradition. We first define a dictionary of relevant/nterms within categories such as raagas, taalas, performers,/ncomposers, and instruments, and create a complex ...
By mining user-generated text content we can obtain musicrelated/ninformation that could not otherwise be extracted/nfrom audio signals or symbolic score representations. In/nthis paper we propose a methodology for extracting/nmusic-related semantic information from an online/ndiscussion forum, rasikas.org, dedicated to the Carnatic/nmusic tradition. We first define a dictionary of relevant/nterms within categories such as raagas, taalas, performers,/ncomposers, and instruments, and create a complex network/nrepresentation by matching such dictionary against the forum/nposts. This network representation is used to identify/npopular terms within the forum, as well as relevant/nco-occurrences and semantic relationships. This way, for/ninstance, we are able to learn the instrument played by a/nperformer with 95% accuracy, to discover the confusion/nbetween two raagas with different naming conventions, or/nto infer semantic relationships regarding lineage or musical/ninfluence. This contribution is a first step towards the/nautomatic creation of ontologies for specific musical cultures.
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