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dc.contributor.authorFrankel, Joe
dc.contributor.authorWester, Mirjam
dc.contributor.authorKing, Simon
dc.coverage.spatial4en
dc.date.accessioned2006-05-09T11:48:50Z
dc.date.available2006-05-09T11:48:50Z
dc.date.issued2004-09
dc.identifier.citationProc. ICSLP, September 2004en
dc.identifier.urihttp://hdl.handle.net/1842/939
dc.description.abstractThis paper describes the use of dynamic Bayesian networks for the task of articulatory feature recognition. We show that by modeling the dependencies between a set of 6 multi-leveled articulatory features, recognition accuracy is increased over an equivalent system in which features are considered independent. Results are comparedto those found using artificial neural networks on an identical task.en
dc.format.extent108166 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.titleArticulatory Feature Recognition Using Dynamic Bayesian Networksen
dc.typeConference Paperen


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