6. A machine translation method comprising: translating an original sentence which is a character string of a first language into a forward-translated sentence which is a character string of a second language; acquiring, by translating an original word in the original sentence corresponding to a first forward-translated word in the forward-translated sentence, at least one second forward-translated word different from the first forward-translated word, to obtain candidate words including the first forward-translated word and the at least one second forward-translated word; calculating a fluency for each of the candidate words, the fluency indicating naturalness of the forward-translated sentence if each of the candidate words is replaced with the first forward-translated word; obtaining at least one reverse-translated word for each of the candidate words by reverse-translating each candidate word into the first language; calculating a semantic similarity between the original word and each reverse-translated word; and selecting a corrected forward-translated word to be replaced with the first forward-translated word from among the candidate words based on the semantic similarity and fluency.
6. A machine translation method comprising: translating an original sentence which is a character string of a first language into a forward-translated sentence which is a character string of a second language; acquiring, by translating an original word in the original sentence corresponding to a first forward-translated word in the forward-translated sentence, at least one second forward-translated word different from the first forward-translated word, to obtain candidate words including the first forward-translated word and the at least one second forward-translated word; calculating a fluency for each of the candidate words, the fluency indicating naturalness of the forward-translated sentence if each of the candidate words is replaced with the first forward-translated word; obtaining at least one reverse-translated word for each of the candidate words by reverse-translating each candidate word into the first language; calculating a semantic similarity between the original word and each reverse-translated word; and selecting a corrected forward-translated word to be replaced with the first forward-translated word from among the candidate words based on the semantic similarity and fluency. 9. The method according to claim 6 , wherein the obtaining the at least one reverse-translated word extracts at least one word of the first language obtained by translating each candidate words as the at least one reverse-translated word.