Learn More
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)
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)
The Computer-Assisted Translation (CAT) paradigm tries to integrate human expertise into the automatic translation process. In this paradigm, a human translator interacts with a translation system that dynamically offers a list of translations that best completes the part of the sentence that is being translated. This human-machine sinergy aims at a double(More)
We address the problem of smoothing the probability distribution defined by a finite state automaton. Our approach extends the ideas employed for smoothing n-gram models. This extension is obtained by interpreting n-gram models as finite state models. The experiments show that our smoothing improves perplexity over smoothed n-grams and Error Correcting(More)
OBJECTIVES To examine the methods to handle marginal readings in the analysis of ambulatory blood pressure. DESIGN Data obtained from automatic ambulatory blood pressure monitoring include several 'outliers', i.e. readings at the frontier of physiologically acceptable ranges. Several methods have been used to handle these readings. We need to know whether(More)
The use of co-trimoxazole in HIV-positive patients has been associated with a high frequency (40-80%) of hypersensitivity reactions. This has been attributed to the bioactivation of the sulphonamide component, sulphamethoxazole (SMX), to its toxic hydroxylamine and nitroso metabolites. The aim of this study was to determine whether functionally significant(More)
Speech-input translation can be properly approached as a pattern recognition problem by means of statistical alignment models and stochastic finite-state transducers. Under this general framework, some specific models are presented. One of the features of such models is their capability of automatically learning from training examples. Moreover, the(More)