Patent Document ID: 8612203
Application ID: 11922311

Base Claim:
1. A method for statistical machine translation using a bilingual sublanguage space, said method comprising; constructing a bilingual sublanguage space by defining a similarity measure between source text and a plurality of joint count tables, each of which corresponding to one or more than one bilingual document pair, identifying a translation unit to be translated from a source language to a target language, defining a source text unit, where said source text unit comprises said translation unit, and mapping said source text unit into a weighted combination of the joint count tables, such that joint count tables corresponding to source language of the bilingual document pairs that are more similar to the source text unit are assigned greater weights, and joint count tables corresponding to source language of the bilingual document pairs that are more dissimilar from the source text unit are assigned lower weights, wherein the joint count tables are used for carrying out statistical machine translation of said translation unit according to the respective weights.

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Claim 5:
5. The method of claim 1 further comprising; providing a language model component adapted to the source text unit; providing a language model component adapted to the source text unit by selecting one or more bilingual document pairs whose source-language portion is similar to the source text unit, and estimating the language model based on the target language portion of said selected bilingual document pair, thereby adapting said language model; providing a language model component adapted to the source text unit by estimating the language model based on the target language portions of clusters of said bilingual document pairs, in dependence on the measure of similarity between the clusters and the source text unit; or providing a language model component adapted to the source text unit by: clustering the collection of bilingual document pairs to assemble document pairs that similarly translate aligned words or aligned phrases of the document pairs; defining a measure of similarity between an arbitrary source text unit and each of the clusters in dependency on translation usages; and associating a language model in the target language with each of the clusters.