This document presents an experiment in the automatic translation of Canadian Court judgments from English to French and from French to English. We show that although the language used in this type of legal text is complex and specialized, an SMT system can produce intelligible and useful translations, provided that the system can be trained on a vast amount of legal text. We also describe the results of a human evaluation of the output of the system.

Notwithstanding machine translation’s impressive progress over the last decade, many translators remain convinced that the output of even the best MT systems is not sufficient to facilitate the production of publication-quality texts. To increase their productivity they turn instead to translator support tools. We examine the use of one such tool: TransSearch, an online bilingual concordancer. From the millions of requests stored in the system’s logs over a 6-year period, we extracted and analyzed the most frequently submitted queries, in an effort to characterize the kinds of problems for which translators turn to this system for help. What we discover, somewhat surprisingly, is that our system seems particularly well-suited to help translate highly polysemous adverbials and prepositional phrases.

Nous offrirons une démonstration de la dernière version de TransCheck, un vérificateur automatique de traductions que le RALI est en train de développer. TransCheck prend en entrée deux textes, un texte source dans une langue et sa traduction dans une autre, les aligne au niveau de la phrase et ensuite vérifie les régions alignées pour s’assurer de la présence de certains équivalents obligatoires (p. ex. la terminologie normalisée) et de l’absence de certaines interdictions de traduction (p. ex. des interférences de la langue source). Ainsi, TransCheck se veut un nouveau type d’outil d’aide à la traduction qui pourra à réduire le fardeau de la révision et diminuer le coût du contrôle de la qualité.

This paper presents the results of the usability evaluations that were conducted within TransType2, an international R&D project the goal of which was to develop a novel approach to interactive machine translation. We briefly sketch the TransType system and then describe the methodology that we elaborated for the five rounds of user trials that were held on the premises of two translation agencies over the last eighteen months of the project. We provide the productivity results posted by the six translators who tested the system and we also discuss some of the non-quantitative factors which influenced the users’ reaction to TransType.

This paper presents TTPlayer, a trace file analysis tool used to develop TransType, an innovative computer-aided translation system. We first discuss the context of the project and the design of the tracing tool. We show how it was used for discovering interesting patterns of use as well to guide further developments in the TT2 project.

TransType2 is a novel kind of interactive MT in which the system and the user collaborate in drafting a target text, the system’s contribution taking the form of predictions that extend what the translator has already typed in. TT2 is also an international research project in which end-users are represented by two translation firms. We describe the contribution of these translators to the project, from their input to the system’s functional specifications to their participation in quarterly user trials. We also present the results of the latest round of user trials.

Our focus is on high-quality (HQ) translation, the worldwide demand for which continues to increase exponentially and now far exceeds the capacity of the translation profession to satisfy it. To what extent is MT currently being used to satisfy this growing demand for HQ translation? Quite obviously, very little. Although MT is being used today by more people than ever before, very few of these users are professional translators. This represents a major change, for a mere ten years ago, translators were still the principal target market for most MT vendors. What happened to bring about this change? For that matter, what happened to most of those MT vendors? The view we present is that the most promising strategy for HQ MT is to embed MT systems in translation environments where the translator retains full control over their output. In our opinion, this new type of interactive MT will achieve better acceptance levels among translators and significantly improve the prospects of MT’s commercial success in the translation industry.

Although undeniably useful for the translation of certain types of repetitive document, current translation memory technology is limited by the rudimentary techniques employed for approximate matching. Such systems, moreover, incorporate no real notion of a document, since the databases that underlie them are essentially composed of isolated sentence strings. As a result, current TM products can only exploit a small portion of the knowledge residing in translators’ past production. This paper examines some of the changes that will have to be implemented if the technology is to be made more widely applicable.

We examine two North American case studies, each of which illustrates a different strategy for coming to terms with high-volume, high-quality translation. The first eschews MT in favour of translation memory technology; the second employs a controlled language to simplify the input to an MT system. Both strategies betray a certain dissatisfaction with the current state of machine translation, although neither alternative, it turns out, fully lives up to its expectations.