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Prefix Probabilities from Stochastic Tree Adjoining Grammars | Mark-Jan Nederhof
; Anoop Sarkar
; Giorgio Satta
; | Date: |
18 Sep 1998 | Journal: | In Proceedings of COLING-ACL ’98 (Montreal) | Subject: | Computation and Language ACM-class: I.2.7; D.3.1 | cs.CL | Affiliation: | DFKI), Anoop Sarkar (UPenn) and Giorgio Satta (UPadova | Abstract: | Language 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. | Source: | arXiv, cs.CL/9809026 | Services: | Forum | Review | PDF | Favorites |
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