High-order hidden Markov modelling

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dc.contributor.authordu Preez J.A.
dc.contributor.authorWeber D.M.
dc.date.accessioned2011-05-15T15:57:30Z
dc.date.available2011-05-15T15:57:30Z
dc.date.issued1998
dc.description.abstractRecently we introduced algorithms for the efficient processing of high-order hidden Markov models (HMMs) of fixed order. In this paper these techniques are generalized to also include mixed-order HMMs. This then allows first-order equivalents to be found for all HMMs, thereby providing a unifying base for reasoning about their properties. Specifically we provide formulations that separates the duration modelling and context modelling capabilities of high-order HMMs.
dc.description.versionArticle
dc.identifier.citationProceedings of the South African Symposium on Communications and Signal Processing, COMSIG
dc.identifier.urihttp://hdl.handle.net/10019.1/10439
dc.subjectAlgorithms
dc.subjectMarkov processes
dc.subjectMathematical models
dc.subjectHidden Markov models (HMM)
dc.subjectSpeech recognition
dc.titleHigh-order hidden Markov modelling
dc.typeArticle
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