Patent ID: 8886514
Filing Date: 2014-11-11
Classification: G06F,G10L

Abstract:
1. A method performed by a computer system for improving a statistical machine translation (SMT) system for translation of text from a given source language into a given target language, said method comprising: 1) receiving at the computer system, a new set of source sentences of the source language; 2) receiving at the computer system, translations of each source sentence in said new set of source sentences into a respective set of hypothesis target sentences of the target language from a machine translation (MT) system; 3) identifying at the computer system, good translations in the respective sets of hypothesis target sentences where a good translation is a hypothesis target sentence having a confidence score higher than a set value, the confidence score for a given hypothesis target sentence being calculated as a posterior probability based on the similarity of that hypothesis with the N−1 other hypotheses in an N-best list generated for the same source sentence, a posterior probability based on the phrase alignment determined by the SMT system, and a language model score for the given hypothesis; 4) retaining said good translations; 5) creating a new parallel bilingual corpus comprising said retained good translations and their corresponding source sentences; 6) training one or more than one component for the SMT system using the new parallel bilingual corpus at the computer system; and 7) adding the newly trained one or more components to original components associated with the SMT system to produce an adapted component with the new and original components kept as a separate components of methods associated with the SMT system; wherein the method employs no human verification.