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Current machine translation (MT) systems are still not perfect. In practice, the output from these systems needs to be edited to correct errors. A way of increasing the productivity of the whole translation process (MT plus human work) is to incorporate the human correction activities within the translation process itself, thereby shifting the MT paradigm(More)
<b>Introduction</b> Translation from a source language into a target language has become a very important activity in recent years, both in official institutions (such as the United Nations and the EU, or in the parliaments of multilingual countries like Canada and Spain), as well as in the private sector (for example, to translate user's manuals or(More)
State-of-the-art machine translation techniques are still far from producing high quality translations. This drawback leads us to introduce an alternative approach to the translation problem that brings human expertise into the machine translation scenario. In this framework, namely Computer Assisted Translation (CAT), human translators interact with a(More)
Computer-Assisted Translation (CAT) is an alternative approach to machine translation, that integrates human expertise into the automatic translation process. In this framework, a human translator interacts with a translation system that dynamically offers a list of translations that best completes the part of the sentence already translated. Stochastic(More)
Current methodologies for automatic translation cannot be expected to produce high quality translations. However, some techniques based on these methodologies can increase the productivity of human translators. The basis of one of these methodolo-gies are finite-state transducers, which are adequate models for computer assisted translation. These models(More)
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