Patent Document ID: 7542893
Application ID: 11431393

Base Claim:
1. A machine translation method for translating source text from a first language to target text in a second language, comprising: receiving the source text in the first language; accessing a library of bi-fragments stored in computer readable memory, each of the bi-fragments including a text fragment from the first language and a text fragment from the second language, at least some of the bi-fragments being modeled as elastic bi-fragments in which words of a fragment are spaced by a gap which is able to assume a variable size corresponding to a number of other words which are to occupy the gap; retrieving text fragments from the second language from the library corresponding to text fragments in the source text; generating, by a processor, at least one target hypothesis, each of said target hypotheses comprising text fragments selected from the second language; and evaluating the target hypothesis with a translation scoring function which scores the target hypothesis according to a plurality of feature functions, at least one of the feature functions comprising a gap size scoring feature which favors hypotheses with statistically more probable gap sizes over hypotheses with statically less probable gap sizes.

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Claim 14:
14. The method of claim 1 , wherein the translation scoring function utilizes a log-linear scoring model of the form: Pr ⁡ ( t 1 J , d 1 K ❘ s 1 I ) = 1 Z f 1 I ⁢ exp ⁢ ∑ m = 1 M ⁢ λ m ⁢ h m ⁡ ( s 1 I , t 1 J , d 1 K ) ( 2 ) to represent the conditional probability of a target sentence t 1 J and an “alignment” d 1 K given a source sentence s 1 I , where each “feature function” h m scores a particular aspect of the relationship between s 1 I and t 1 J , a contribution of each feature function being determined by a weight λ m ; and where z f 1 I is a normalization constant and where at least one of the feature functions h m is selected from: (1) a “bi-fragment” feature h bf , of the general form: h bf ⁡ ( s 1 I , t 1 J , d 1 K ) = ∑ k = 1 K ⁢ log ⁢ ⁢ Pr ⁡ ( target ⁡ ( d k ) ❘ source ⁡ ( d k ) ) , ( 3 ) where Pr(target(d k )|source(d k )) represents a conditional probability of a target fragment given a source fragment, irrespective of their gap sizes; and (2) a gap size scoring feature (h ELAST ), of the general form: h ELAST ⁡ ( s 1 I , t 1 J , d 1 K ) = ∑ k = 1 K ⁢ EL ⁡ ( target ⁡ ( d k ) , source ⁡ ( d k ) ) where EL represents a logarithm of a probability of observing a certain configuration of gap sizes in the target and source fragments of a bi-fragment.