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Clustering acoustic segments using multi- stage agglomerative hierarchical clustering

dc.contributor.authorLerato, Leratoen_ZA
dc.contributor.authorNiesler, Thomasen_ZA
dc.date.accessioned2016-08-18T09:27:06Z
dc.date.available2016-08-18T09:27:06Z
dc.date.issued2015
dc.identifier.citationLerato, L. & Niesler, T. 2015. Clustering acoustic segments using multi- stage agglomerative hierarchical clustering. PLoS ONE 10(10):1-24, doi:10.1371/journal.pone.0141756
dc.identifier.issn1932-6203 (online)
dc.identifier.otherdoi:10.1371/journal.pone.0141756
dc.identifier.urihttp://hdl.handle.net/10019.1/99401
dc.descriptionCITATION: Lerato, L. & Niesler, T. 2015. Clustering acoustic segments using multi- stage agglomerative hierarchical clustering. PLoS ONE 10(10):1-24, doi:10.1371/journal.pone.0141756.
dc.descriptionThe original publication is available at http://journals.plos.org/plosone
dc.description.abstractAgglomerative hierarchical clustering becomes infeasible when applied to large datasets due to its O(N2) storage requirements. We present a multi-stage agglomerative hierarchical clustering (MAHC) approach aimed at large datasets of speech segments. The algorithm is based on an iterative divide-and-conquer strategy. The data is first split into independent subsets, each of which is clustered separately. Thus reduces the storage required for sequential implementations, and allows concurrent computation on parallel computing hardware. The resultant clusters are merged and subsequently re-divided into subsets, which are passed to the following iteration. We show that MAHC can match and even surpass the performance of the exact implementation when applied to datasets of speech segments.en_ZA
dc.description.abstractAFRIKAANSE OPSOMMING: Geen opsomming beskikbaaraf_ZA
dc.description.urihttp://journals.plos.org/plosone/article?id=10.1371/journal.pone.0141756
dc.format.extent24 pagesen_ZA
dc.language.isoen_ZAen_ZA
dc.publisherPublic Library of Scienceen_ZA
dc.subjectAgglomerations, Industrialen_ZA
dc.subjectDocument clusteringen_ZA
dc.subjectAcoustical engineeringen_ZA
dc.titleClustering acoustic segments using multi- stage agglomerative hierarchical clusteringen_ZA
dc.typeArticleen_ZA
dc.description.versionPublisher's version
dc.rights.holderAuthors retain copyrighten_ZA


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