[PDF] Top 20 Prefix Probability for Probabilistic Synchronous Context Free Grammars

... computing prefix probabilities is formulated in quite different terms from the solutions by Jelinek and Lafferty (1991) and by Stolcke (1995) for probabilistic context-free ...of prefix ... See full document

... of probabilistic linear context-free rewriting systems ...the probabilistic simple RCGs discussed by Maier and Søgaard (2008) and by Kallmeyer and Maier (2010), and probabilistic ... See full document

... Probabilistic context-free grammars are one of the most widely used formalisms in current work in sta- tistical natural language parsing and stochastic lan- guage ...bilistic ... See full document

... We have presented an approach to unsuper- vised learning and automatic detection of sylla- ble boundaries and grapheme-to-phoneme con- version using the standard probability model. Automatic conversion of a string ... See full document

... However, this result does not completely settle the question about the expressive power of WCFGs and PCFGs. As we show herein, a WCFG can define a conditional distribution from strings to trees even if it does not define ... See full document

... Our definition of PFAs amounts to a slight loss of generality with respect to standard definitions, in that there are no epsilon transitions and no probability func- tion on states being final. We want to avoid ... See full document

... The assignment of probabilities to the productions of a context-free grammar may generate an improper distribution: the probability of all finite parse trees is less than one.. The condi[r] ... See full document

... of probabilistic grammars from infinite ...input probabilistic finite automaton from an infinite tree distribution specified by means of an input probabilistic context-free ...a ... See full document

... Firstly, probabilistic modeling/training of context- free grammars is theoretically well-understood and can be effectively done in practice, using the inside- outside algorithm (Lari and ... See full document

... We describe an extension of Earley's parser for stochastic context-free grammars that computes the following quantities given a stochastic context-free grammar and an input string: a pro[r] ... See full document

... This paper investigates some computa- tional problems associated with proba- bilistic translation models that have re- cently been adopted in the literature on machine translation. These models can be viewed as pairs of ... See full document

... eral idea is to use a simple and fast decoding algo- rithm to constrain the search space of a following more complex and slower technique. More specif- ically, a bigram decoding pass is executed forward and backward to ... See full document

... of synchronous context-free grammars to handle multiple tar- gets, and describe methods for rule extraction, scoring, pruning, and search with these mod- ... See full document

... Stochastic unification-based grammars (SUBGs) define exponential distributions over the parses generated by a unification- based grammar (UBG). Existing algo- rithms for parsing and estimation require the ... See full document

... The generation is accomplished by use of production rules, belonging to a set 2"4, that rewrite individual phrase markers as sequences of phrase markers or words.. That is, only the foll[r] ... See full document

... parsing to go from abutting below the ~eftmost bottom edge of a domino to the next bottom edge at least one input must be matched against, so as there is only a finite number of input sy[r] ... See full document

... adjoining grammars (TAG) were invented in (Joshi et ...in synchronous TAG ...2006) probabilistic syn- chronous tree insertion grammars (pSTIG) were discussed as model of MT; a tree insertion ... See full document

... The Viterbi approximation is efficient, but it ig- nores most of the derivations in the hypergraph. We implemented variational decoding (Li et al., 2009b), which works as follows. First, given a for- eign string (or ... See full document

... Other formal models that are currently used to implement probabilistic language models such as finite-state automata and context-free grammars are by now well-understood. A fair share of their ... See full document

... regular grammars or Perl- style regular expressions (which are slightly more expres- sive than regular grammars), and they tend to handle cases that need greater expressiveness with the cascade applica- ... See full document