This paper discusses an informal methodology for evaluating Machine Translation software documentation with reference to a case study, in which a number of currently available MT packages are evaluated. Different types of documentation style are discussed, as well as different user profiles. It is found that documentation is often inadequate in identifying the level of linguistic background and knowledge necessary to use translation software, and in explaining technical (linguistic) terms needed to use the software effectively. In particular, the level of knowledge and training needed to use the software is often incompatible with the user profile implied by the documentation. Also, guidance on how to perform more complex tasks, which may be especially idiosyncratic, is often inadequate or missing altogether.

“Embedded” machine translation (MT) refers to an end-to-end computational process of which MT is one of the components. Integrating these components and evaluating the whole has proved to be problematic. As an example of embedded MT, we describe a prototype system called Falcon, which permits paper documents to be scanned and translated into English. MT is thus embedded in the preprocessing of hardcopy pages and subject to its noise. Because Falcon is intended for use by people in the military who are trying to screen foreign documents, and not to understand them in detail, its application makes low demands on translation quality. We report on a series of user trials that speak to the utility of embedded MT in army tasks.

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.