MT Express

The machine translation systems that are being developed at CRL are designed for assimilation purposes and are targeted at a large variety of source texts, including news articles, Web pages, newsgroups articles and email traffic. Thus, coverage and robustness are emphasized over depth of analysis, and accuracy over stylistic fluidity. Moreover, these systems are for the most part developed under severe resource constraints. Some of the new languages which are or will be covered are so-called ‘low-density languages’: languages for which there are little or no electronic resources, comparatively little expertise and few descriptive linguistic works published. An example of such a language under development at CRL is Persian. The lack of electronic resources, including bilingual corpora or even monolingual corpora rules out statistical and learning-based approaches to machine translation. As a consequence, language resources are carefully structured and the organized to support rapid and large scale acquisition of resources (computational dictionaries and grammars). Robustness is also a fundamental issue, and the architecture of the machine translation system itself is designed to produce translations even with incomplete resources (although breadth of lexical coverage is a minimum requirement). One of the desiderata of the MT design is the ability to produce translations after a very short period of development: the incremental addition of linguistic knowledge in the system improves the translation quality without the need to restructure already acquired knowledge. In this paper, we illustrate how the chosen structuration of the language resources supports on the one hand rapid and incremental acquisition of resources and enables robust processing on the other hand.