Learning translation relationships among words

A method of training a machine translation system, comprising:

• obtaining a corpus of aligned, bilingual multi-word units;
• calculating word association scores for word pairs in the corpus based on co-occurrence of words in the aligned units;
• identifying hypothesized compounds based on an absence of one-to-one correspondence between words in the aligned units;
• providing a rewritten corpus in which the hypothesized compounds have been replaced by fused tokens;
• re-calculating the word association scores using the rewritten corpus;
• generating transfer mappings that map from words and fused tokens in one language to words and fused tokens in another language, based on the selected translation relationships;
• filtering the transfer mappings based on at least one of:
• frequency of appearance;
• completeness of parses of the multi-word units;
• or completeness of alignment of multi-word units;
• and
• training the machine translation system based on the filtered transfer mappings.

A computer-readable medium comprising computer-executable instructions which, when executed by a computer, configure the computer to:

• calculate word association scores for word pairs based on co-occurrences of words in each of a plurality of sets of aligned, bilingual units in a corpus;
• identify hypothesized compounds in the units based on word association scores that indicate a lack of one-to-one correspondence between words in the first unit and words in the second unit;
• re-calculate the word association scores based on co-occurrences of words and hypothesized compounds;
• rank the word pairs based on the re-calculated word association scores;
• and
• generate transfer mappings that map from words and hypothesized compounds in one language to words and hypothesized compounds in another language, based on the ranking of the re-calculated word association scores.