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Nowadays, the most successful speech recognition systems are based on stochastic finite-state networks (hidden Markov models and n-grams). Speech translation can be accomplished in a similar way as speech recognition. Stochastic finite-state transducers, which are specific stochastic finitestate networks, have proved very adequate for translation modeling.(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)
Formal translations constitute a suitable framework for dealing with many problems in pattern recognition and computational linguistics. The application of formal transducers to these areas requires a stochastic extension for dealing with noisy, distorted patterns with high variability. In this paper, some estimation criteria are proposed and developed for(More)
Statistical techniques have experienced an increasing interest by the natural language research community in the last years and have proved powerful possibilities for extracting useful information from translation examples. Both statistical language modeling and statistical machine translation are well-established disciplines with solid basis and(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 methodologies are finite-state transducers, which are adequate models for computer assisted translation. These models have(More)
In the current European scenario, characterized by the coexistence of communities writing and speaking a great variety of languages, machine translation has become a technology of capital importance. In areas of Spain and of other countries, coofficiality of several languages implies producing several versions of public information. Machine translation(More)
Statistical techniques and grammatical inference have been used for dealing with automatic speech recognition with success, and can also be used for speech-to-speech machine translation. In this paper, new advances on a method for finite-state transducer inference are presented. This method has been tested experimentally in a speech-input translation task(More)