Look-Back and Look-Ahead in the Conversion of Hidden Markov Models into Finite State Transducers

dc.creatorKempe, Andre
dc.date1998-02-02
dc.date.accessioned2026-07-07T02:36:12Z
dc.date.available2026-07-07T02:36:12Z
dc.descriptionThis paper describes the conversion of a Hidden Markov Model into a finite state transducer that closely approximates the behavior of the stochastic model. In some cases the transducer is equivalent to the HMM. This conversion is especially advantageous for part-of-speech tagging because the resulting transducer can be composed with other transducers that encode correction rules for the most frequent tagging errors. The speed of tagging is also improved. The described methods have been implemented and successfully tested.
dc.description9 pages, A4, LaTeX (+4x eps) gzip tar gzip uuencode
dc.identifierhttps://arxiv.org/abs/cmp-lg/9802001
dc.identifierhttp://arxiv.org/abs/cmp-lg/9802001
dc.identifierNeMLaP3/CoNLL'98, pp.29-37, Sydney, Australia. January 15-17, 1998
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/15827
dc.subjectComputation and Language
dc.titleLook-Back and Look-Ahead in the Conversion of Hidden Markov Models into Finite State Transducers
dc.typetext

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