The customization of Machine Translation systems concentrates, for the most part, on MT dictionaries. In this paper, we focus on the customization of complex lexical entries that involve various types of lexical collocations, such as sub-categorization frames. We describe methods and tools that leverage existing parsers and other MT dictionaries for customization of MT dictionaries. This customization process is applied on large-scale customization of several commercial MT systems, including English to Japanese, Chinese, and Korean.

We present an implementation of the notion of modularity and composition applied to unification based grammars. Monolithic unification grammars can be decomposed into sub-grammars with well defined interfaces. Sub-grammars are applied in a sequential manner at runtime, allowing incremental development and testing of large coverage grammars. The modular approach to grammar development leads us away from the traditional view of parsing a string of input symbols as the recognition of some start symbol, and towards a richer and more flexible view where inputs and outputs share the same structural properties.

The Computing Research Laboratory is currently developing technologies that allow rapid deployment of automatic translation capabilities. These technologies are designed to handle low-density languages for which resources, be that human informants or data in electronically readable form, are scarce. All tools are built in an incremental fashion, such that some simple tools (a bilingual dictionary or a glosser) can be delivered early in the development to support initial analysis tasks. More complex applications can be fielded in successive functional versions. The technology we demonstrate has first been applied to Persian-English machine translation within the Shiraz project and is currently extended to cover languages such as Arabic, Japanese, Korean and others.

We describe a Machine Translation framework aimed at the rapid development of large scale robust machine translation systems for assimilation purposes, where the MT system is incorporated as one of the tools in an analyst’s workstation. The multilevel architecture of the system is designed to enable early delivery of functional translation capabilities and incremental improvement of quality. A crucial aspect of the framework is a careful articulation of a software architecture, a linguistic architecture and an incremental development process of linguistic knowledge.