Adattamento al Progetto dei Modelli di Traduzione Automatica nella Traduzione Assistita
Authors: Mauro Cettolo, Nicola Bertoldi, Marcello Federico (Fondazione Bruno Kessler, 2014)
Topic: Machine Translation

Abstract
The integration of automatic translation into axi-stite translation systems is a challenge for both aqua-demic and industrial research. Professional translators perceive the ability of self-mathic systems to adapt to their style and corrections as crucial. In this article I proposed a scheme of adaptation of automatic translation sides to a specific document based on a limited amount of text, manually corrected, equal to that produced daily by a single translator.

Introduction
Despite the significant and continued progress, the automatic translation (TA) is not yet able to generate text suitable for publication without human intervention. On the other hand, many studies have confirmed that in the context of assisted translation the correction of translated texts automatically enables an increase in the productivity of professional translators (see paragraph 2). This application of the TA is as more effective as greater and the integration of the automatic translation system into the entire translation process, which can be achieved by specializing the system both to the specific text to be translated and to the characteristics of the specific translator and its corrections. In the translation industry, the typical scenario is that of one or more translators who work for a few days on a given translation project, or on a set of homogeneous documents. After a working day, the information contained in the newly translated texts and the corrections made by the translators can be entered into the automatic system with the aim of improving the quality of the automatic translations proposed the next day. We will call this process adaptation to the project. The adaptation to the project can be repeated daily until the end of the work, so that all the information that implicitly translators put at the disposal of the system can be best exploited. This article presents one of the results of the European MateCat project,1 in which we have developed a web-based assisted translation system that integrates a TA module that is self-adjusted to the specific project. The validation experiments we will illustrate have been conducted on four languages, from English to Italian (IT), French (FR), Spanish (ES) and German (DE), and in two fields, Information and Communication Technologies (ICT) and Legal (LGL). Ideally, the proposed adaptation methods should be evaluated by measuring the profit in terms of productivity on real translation projects. Therefore, as far as possible, we have conducted assessments on the field where professional translators have corrected the hypothesized translations by automatic, adjusted and non-adjusted systems. The adjustment was carried out on the basis of a part of the project translated during a preliminary phase, in which the same translator was asked to correct the translations provided by an unadjusted starting system. Since field assessments are extremely expensive, they cannot be performed frequently to compare all possible variants of algorithms and processes. We also conducted laboratory assessments, where the corrections of translators were simulated by reference translations. In general, in the legal field the improvements observed in the laboratory anticipated those measured in the field. On the contrary, the results in the ICT domain were controversial due to the little correspondence between the texts used for adaptation and those actually translated during the experiment.

Conclusion
A current research topic for the assisted translation industry is how to do-to automatic translation systems of the layer-city of self-adaptation. In this work I have presented a scheme of self-adaptation and the results of its validation not only in lab outlets but also on the field, with coin-wishing of professional translators, thanks to the collaboration with the industrial partner of MateCat. The experimental results confirmed the impact of our proposal, with gauge-day productivity up to 43%. However, the me-all works only if the texts used as the basis for the selection of specific data on which to perform the a-date is representative of the document you want to translate. In fact, if such a condition was not verified, as it was in our English-French/ICT experiments, the adapted models may be unable to improve the starting ones; in any case even in these critical conditions we have noticed any deterioration of performance, demonstrating the conservative behavior of our scheme.