We present four kinds of machine translation system in this description: E-K (English to Korean), K-E (Korean to English), J-K (Japanese to Korean), K-J (Korean to Japanese). Among these, E-K and K-J translation systems are published commercially, and the other systems have finished their development. This paper describes the structure and function of each system with figures and translation results.

A statistical method for compound noun decomposition is presented. Previous studies on this problem showed some statistical information are helpful. But applying statistical information was not so systemic that performance depends heavily on the algorithm and some algorithms usually have many separated steps. In our work statistical information is collected from manually decomposed compound noun corpus to build a Markov model for composition. Two Markov chains representing statistical information are assumed independent: one for the sequence of participants' lengths and another for the sequence of participants ' features. Besides Markov assumptions, least participants preference assumption also is used. These two assumptions enable the decomposition algorithm to be a kind of conditional dynamic programming so that efficient and systemic computation can be performed. When applied to test data of size 5027, we obtained a precision of 98.4%.

The Unification-based Grammars seem to be adequate for the analysis of agglutinative languages such as Korean, etc. In this paper, the merits of Lexical Functional Grammar is analyzed and the structure of Korean Syntactic Analyzer is described. Verbal complex category is used for the analysis of several linguistic phenomena and a new attribute of UNKNOWN is defined for the analysis of grammatical relations.