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dc.contributor.authorMolloy, Laurence
dc.contributor.authorIsard, Stephen
dc.coverage.spatial4en
dc.date.accessioned2006-05-11T16:54:25Z
dc.date.available2006-05-11T16:54:25Z
dc.date.issued1998-12
dc.identifier.citationIn ICSLP-1998, paper 1103.en
dc.identifier.urihttp://www.isca-speech.org/archive/icslp_1998/index.html
dc.identifier.urihttp://hdl.handle.net/1842/1024
dc.description.abstractIn this paper a method of integrating a model of suprasegmental duration with a HMM-based recogniser at the post-processing level is presented. The N-Best utterance output is rescored using a suitable linear combination of acoustic log-likelihood (provided by a set of tied-state triphone HMMs) and duration log-likelihood (provided by a set of durational models). The durational model used in the post-processing imposes syllable-level elastic constraints on the durational behaviour of speech segments. Results are presented for word accuracy on the Resource Management database after rescoring, using two different syllable-like constraint units, a fixed-size N-phone window and simple (no constraint) phone duration probability scoring.en
dc.format.extent55974 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherInternational Speech Communication Associationen
dc.titleSuprasegmental Duration Modelling with Elastic Constraints in Automatic Speech Recognitionen
dc.typeConference Paperen


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