1. A computer-implemented method comprising: generating a plurality of machine translation systems using a single machine translation engine, the generating including: for each machine translation system of the plurality of machine translation systems, training the machine translation system on differing, randomly sampled portions of a common training corpus; generating a plurality of candidate machine translations, wherein each candidate machine translation of the plurality of candidate machine translations is output from a respective machine translation system of the plurality of machine translation systems; determining a degree of correlation between two or more machine translation systems of the plurality of the machine translation systems; when the degree of correlation between the two or more machine translation systems is less than a threshold indicative of a minimum acceptable gain in translation quality achievable by the two or more machine translation systems, combining the candidate machine translations of the two or more candidate machine translations; and generating a consensus translation based on the combined machine translations.
1. A computer-implemented method comprising: generating a plurality of machine translation systems using a single machine translation engine, the generating including: for each machine translation system of the plurality of machine translation systems, training the machine translation system on differing, randomly sampled portions of a common training corpus; generating a plurality of candidate machine translations, wherein each candidate machine translation of the plurality of candidate machine translations is output from a respective machine translation system of the plurality of machine translation systems; determining a degree of correlation between two or more machine translation systems of the plurality of the machine translation systems; when the degree of correlation between the two or more machine translation systems is less than a threshold indicative of a minimum acceptable gain in translation quality achievable by the two or more machine translation systems, combining the candidate machine translations of the two or more candidate machine translations; and generating a consensus translation based on the combined machine translations. 2. The method of claim 1 , where the portions of the common training corpus for the machine translation systems are of equal size.