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dc.contributor.authorForsyth, Mark
dc.contributor.authorJack, Mervyn A
dc.coverage.spatial4en
dc.date.accessioned2006-05-18T14:31:36Z
dc.date.available2006-05-18T14:31:36Z
dc.date.issued1994-04
dc.identifier.citationAcoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on, Volume i, 19-22 April 1994 Page(s):I/313 - I/316.en
dc.identifier.govdocDigital Object Identifier 10.1109/ICASSP.1994.389293
dc.identifier.issn1520-6149
dc.identifier.urihttp://ieeexplore.ieee.org/
dc.identifier.urihttp://hdl.handle.net/1842/1117
dc.description.abstractThis paper describes the use of a multiple codebook SCHMM speaker verification system, which uses a novel technique for discriminative hidden Markov modelling known as discriminative observation probabilities (DOP). DOP can easily be added to a multiple codebook HMM system and require minimal additional computation and no additional training. The DOP technique can be applied to both speech and speaker recognition. Results are presented for text-dependent experiments on isolated digits from 27 true speakers and 84 casual imposters, recorded over the public telephone network in the United Kingdom. DOP are shown to significantly improve speaker verification performance for several commonly used parameter sets.en
dc.format.extent366905 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherIEEEen
dc.titleDiscriminating semi-continuous HMM for speaker verificationen
dc.typeConference Paperen


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