A Statistical Model for Word Discovery in Transcribed Speech

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dc.creatorVenkataraman, Anand
dc.date2001-11-30
dc.date.accessioned2026-07-07T03:17:59Z
dc.date.available2026-07-07T03:17:59Z
dc.descriptionA statistical model for segmentation and word discovery in continuous speech is presented. An incremental unsupervised learning algorithm to infer word boundaries based on this model is described. Results of empirical tests showing that the algorithm is competitive with other models that have been used for similar tasks are also presented.
dc.descriptionExpanded version of ICML-01 paper (pp.569--576)
dc.identifierhttps://arxiv.org/abs/cs/0111065
dc.identifierhttp://arxiv.org/abs/cs/0111065
dc.identifierComputational Linguistics, 27(3), pp.352--372, 2001
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/30937
dc.subjectComputation and Language
dc.subjectI.2.6;I.2.7
dc.titleA Statistical Model for Word Discovery in Transcribed Speech
dc.typetext

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