A Bootstrap Approach to Automatically Generating Lexical Transfer Rules

We describe a method for automatically generating Lexical Transfer Rules (LTRs) from word equivalences using transfer rule templates. Templates are skeletal LTRs, unspecified for words. New LTRs are created by instantiating a template with words, provided that the words belong to the appropriate lexical categories required by the template. We define two methods for creating an inventory of templates and using them to generate new LTRs. A simpler method consists of extracting a finite set of templates from a sample of hand coded LTRs and directly using them in the generation process. A further method consists of abstracting over the initial finite set of templates to define higher level templates, where bilingual equivalences are defined in terms of correspondences involving phrasal categories. Phrasal templates are then mapped onto sets of lexical templates with the aid of grammars. In this way an infinite set of lexical templates is recursively defined. New LTRs are created by parsing input words, matching a template at the phrasal level and using the corresponding lexical categories to instantiate the lexical template. The definition of an infinite set of templates enables the automatic creation of LTRs for multi-word, non-compositional word equivalences of any cardinality.

Explanation-based Learning for Machine Translation

In this paper we present an application of explanation-based learning (EBL) in the parsing module of a real-time English-Spanish machine translation system designed to translate closed captions. We discuss the efficiency/coverage trade-offs available in EBL and introduce the techniques we use to increase coverage while maintaining a high level of space and time efficiency. Our performance results indicate that this approach is effective.

A Unified Example-Based and Lexicalist Approach to Machine Translation

We present an approach to Machine Translation that combines the ideas and methodologies of the Example-Based and Lexicalist theoretical frameworks. The approach has been implemented in a multilingual Machine Translation system.