2004 Volume 11 Issue 2 Pages 101-113
As part of an attempt of revealing what kind of technical challenges must be solved to improve the quality of machine translation up to the extent of human translation, this paper carries out a quantitative analysis of distribution of familiarity rating of verbs between machine-translated Japanese sentences and human-translated ones, both of which are obtained from English sentences selected randomly from news articles. The familiarity rating is measured based on the database of familiarity rating developed at NTT Communication Science Laboratories.The analysis found that no significant difference exists in the distribution of familiarity rating of verbs between machine-and human-translated sentences. This intimates that as far as concerning the translation of verbs alone, the quality of the investigated MT system has reached a fixed standard.
