Prefix Probabilities from Stochastic Tree Adjoining Grammars

dc.creatorNederhof, Mark-Jan
dc.creatorSarkar, Anoop
dc.creatorSatta, Giorgio
dc.date1998-09-18
dc.date.accessioned2026-07-07T03:23:32Z
dc.date.available2026-07-07T03:23:32Z
dc.descriptionLanguage models for speech recognition typically use a probability model of the form Pr(a_n | a_1, a_2, ..., a_{n-1}). Stochastic grammars, on the other hand, are typically used to assign structure to utterances. A language model of the above form is constructed from such grammars by computing the prefix probability Sum_{w in Sigma*} Pr(a_1 ... a_n w), where w represents all possible terminations of the prefix a_1 ... a_n. The main result in this paper is an algorithm to compute such prefix probabilities given a stochastic Tree Adjoining Grammar (TAG). The algorithm achieves the required computation in O(n^6) time. The probability of subderivations that do not derive any words in the prefix, but contribute structurally to its derivation, are precomputed to achieve termination. This algorithm enables existing corpus-based estimation techniques for stochastic TAGs to be used for language modelling.
dc.description7 pages, 2 Postscript figures, uses colacl.sty, graphicx.sty, psfrag.sty
dc.identifierhttps://arxiv.org/abs/cs/9809026
dc.identifierhttp://arxiv.org/abs/cs/9809026
dc.identifierIn Proceedings of COLING-ACL '98 (Montreal)
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/32976
dc.subjectComputation and Language
dc.subjectI.2.7; D.3.1
dc.titlePrefix Probabilities from Stochastic Tree Adjoining Grammars
dc.typetext

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