Expoiting Syntactic Structure for Language Modeling

dc.creatorChelba, Ciprian
dc.creatorJelinek, Frederick
dc.date1998-11-12
dc.date2000-01-25
dc.date.accessioned2026-07-07T03:23:49Z
dc.date.available2026-07-07T03:23:49Z
dc.descriptionThe paper presents a language model that develops syntactic structure and uses it to extract meaningful information from the word history, thus enabling the use of long distance dependencies. The model assigns probability to every joint sequence of words--binary-parse-structure with headword annotation and operates in a left-to-right manner --- therefore usable for automatic speech recognition. The model, its probabilistic parameterization, and a set of experiments meant to evaluate its predictive power are presented; an improvement over standard trigram modeling is achieved.
dc.descriptionchanged ACM-class membership and buggy author names
dc.identifierhttps://arxiv.org/abs/cs/9811022
dc.identifierhttp://arxiv.org/abs/cs/9811022
dc.identifierProceedings of ACL'98, Montreal, Canada
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/33092
dc.subjectComputation and Language
dc.subjectG.3, I.2.7, I.5.1, I.5.4
dc.titleExpoiting Syntactic Structure for Language Modeling
dc.typetext

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