Abstract: A method and a system for making merging decisions for a translation are disclosed which are suited to use where the target language is a productive compounding one. The method includes outputting decisions on merging of pairs of words in a translated text string with a merging system. The merging system can include a set of stored heuristics and/or a merging model. In the case of heuristics, these can include a heuristic by which two consecutive words in the string are considered for merging if the first word of the two consecutive words is recognized as a compound modifier and their observed frequency f1 as a closed compound word is larger than an observed frequency f2 of the two consecutive words as a bigram. In the case of a merging model, it can be one that is trained on features associated with pairs of consecutive tokens of text strings in a training set and predetermined merging decisions for the pairs.

Abstract: A translation system and method for translating source text from a first language to target text in a second language are disclosed. A library of bi-phrases is accessed to retrieve bi-phrases which each match a part of the source text. Each of the bi-phrases includes respective text fragments from the first and second language. Words of some (or all) of the bi-phrases are tagged with restricted part of speech (RPOS) tags. At least one of the RPOS tags is configured for identifying a word from the second language as being one which also forms a part of a closed compound word in the library. At least one target hypothesis is generated from the bi-phrases, which includes text fragments in the second language. The target hypothesis or hypotheses are evaluated, based at least in part on combinations of the restricted part of speech tags. Based on the evaluation, one of the at least one target hypothesis is output as the optimal hypothesis for forming the translation.

Abstract: A method and a system for making merging decisions for a translation are disclosed which are suited to use where the target language is a productive compounding one. The method includes outputting decisions on merging of pairs of words in a translated text string with a merging system. The merging system can include a set of stored heuristics and/or a merging model. In the case of heuristics, these can include a heuristic by which two consecutive words in the string are considered for merging if the first word of the two consecutive words is recognized as a compound modifier and their observed frequency f1 as a closed compound word is larger than an observed frequency f2 of the two consecutive words as a bigram. In the case of a merging model, it can be one that is trained on features associated with pairs of consecutive tokens of text strings in a training set and predetermined merging decisions for the pairs.

Abstract: A translation system and method for translating source text from a first language to target text in a second language are disclosed. A library of bi-phrases is accessed to retrieve bi-phrases which each match a part of the source text. Each of the bi-phrases includes respective text fragments from the first and second language. Words of some (or all) of the bi-phrases are tagged with restricted part of speech (RPOS) tags. At least one of the RPOS tags is configured for identifying a word from the second language as being one which also forms a part of a closed compound word in the library. At least one target hypothesis is generated from the bi-phrases, which includes text fragments in the second language. The target hypothesis or hypotheses are evaluated, based at least in part on combinations of the restricted part of speech tags. Based on the evaluation, one of the at least one target hypothesis is output as the optimal hypothesis for forming the translation.