The theme of controlled translation is currently in vogue in the area of MT. Recent research (Sch aler et al., 2003; Carl, 2003) hypothesises that EBMT systems are perhaps best suited to this challenging task. In this paper, we present an EBMT system where the generation of the target string is filtered by data written according to controlled language specifications. As far as we are aware, this is the only research available on this topic. In the field of controlled language applications, it is more usual to constrain the source language in this way rather than the target. We translate a small corpus of controlled English into French using the on-line MT system Logomedia, and seed the memories of our EBMT system with a set of automatically induced lexical resources using the Marker Hypothesis as a segmentation tool. We test our system on a large set of sentences extracted from a Sun Translation Memory, and provide both an automatic and a human evaluation. For comparative purposes, we also provide results for Logomedia itself.

We describe the authoring tool, EasyEnglish, which is part of IBM's internal SGML editing environment, Information Development Workbench. EasyEnglish helps writers produce clearer and simpler English by pointing out ambiguity and complexity as well as performing some standard grammar checking. Where appropriate, EasyEnglish makes suggestions for rephrasings that may be substituted directly into the text by using the editor interface. EasyEnglish is based

This paper presents a grammar diagnostic system for controlled language checking. The implemented diagnostics were designed to address the most difficult rewrites for authors, based on an empirical analysis of log files containing over 180,000 sentences. The design and implementation of the diagnostic system are presented, along with experimental results from an empirical evaluation of the completed system.

We argue that it is useful for a machine translation system to be able to provide the user with an estimate of the translation quality for each sentence. This makes it possible for bad translations to be filtered out before post-editing, to be highlighted by the user interface, or to cause an interactive system to ask for a rephrasing. A system providing such an estimate is described, and examples from its practical application to an MT system are given. 1

This paper summarizes the goals of controlled language authoring for machine translation, and discusses why automatic rewriting is an important research area for controlled authoring 1 . We present the KANT controlled language rewriting architecture, which combines a rewriting engine with interactive dialogue.

This paper presents a source language diagnostic system for controlled translation. Diagnostics were designed and implemented to address the most difficult rewrites for authors, based on an empirical analysis of log files containing over 180,000 sentences. The design and implementation of the diagnostic system are presented, along with experimental results from an empirical evaluation of the completed system. We found that the diagnostic system can correctly identify the problem in 90.2% of the cases. In addition, depending on the type of grammar problem, the diagnostic system may offer a rewritten sentence. We found that 89.4% of the rewritten sentences were correctly rewritten. The results suggest that these methods could be used as the basis for an automatic rewriting system in the future.

One key to the success of EBMT is the removal of the boundaries limiting the potential of translation memories (TMs). We discuss a linguistically enhanced TM system, a Phrasal Lexicon (PL), which takes advantage of the huge, underused resources available in existing translation aids. We claim that PL and EBMT systems can only provide valuable translation solutions for restricted domains, especially where controlled language restrictions are imposed. When integrated into a hybrid and/or multi-engine MT environment, the PL will yield significant improvements in translation quality. We establish a future model of translation usage and anticipate that EBMT and the PL will have a central place in future hybrid integrated translation platforms.

This paper presents a source language diagnostic system for controlled translation. Diagnostics were designed and implemented to address the most difficult rewrites for authors, based on an empirical analysis of log files containing over 180,000 sentences. The design and implementation of the diagnostic system are presented, along with experimental results from an empirical evaluation of the completed system. We found that the diagnostic system can correctly identify the problem in 90.2% of the cases. In addition, depending on the type of grammar problem, the diagnostic system may offer a rewritten sentence. We found that 89.4% of the rewritten sentences were correctly rewritten. The results suggest that these methods could be used as the basis for an automatic rewriting system in the future.

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