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dc.contributor.authorWester, Mirjam
dc.contributor.authorKessens, Judith M
dc.contributor.authorStrik, Helmer
dc.coverage.spatial4en
dc.date.accessioned2006-05-11T13:10:21Z
dc.date.available2006-05-11T13:10:21Z
dc.date.issued2000-10
dc.identifier.citationIn ICSLP-2000, vol.4, 488-491.en
dc.identifier.urihttp://www.isca-speech.org/archive/icslp_2000
dc.identifier.urihttp://hdl.handle.net/1842/986
dc.description.abstractThis paper describes how the performance of a continuous speech recognizer for Dutch has been improved by modeling within-word and cross-word pronunciation variation. A relative improvement of 8.8% in WER was found compared to baseline system performance. However, as WERs do not reveal the full effect of modeling pronunciation variation, we performed a detailed analysis of the differences in recognition results that occur due to modeling pronunciation variation and found that indeed a lot of the differences in recognition results are not reflected in the error rates. Furthermore, error analysis revealed that testing sets of variants in isolation does not predict their behavior in combination. However, these results appeared to be corpus dependent.en
dc.format.extent35503 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherInternational Speech Communication Associationen
dc.titlePronunciation Variation in ASR: Which Variation to Model?en
dc.typeConference Paperen


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