Translation capability of a Phrase-Based Statistical Machine Translation (PBSMT) system mostly depends on parallel data and phrases that are not present in the training data are not correctly translated. This paper describes a method that efflciently expands the existing knowledge…

This paper present the structure, function and performance of SPOST, a broad coverage, rule-based part-of-speech tagger developed as a component of the Pagnlyzer Spanish Analysis Component of the Pangloss Knowledge-based Machine Translation System. It also describes preparations for the general…

En el marco de la traducción automática árabe-inglés, el enfoque pseudointerlingüístico de UniArab ha logrado, incluso con oraciones simples, mejores resultados que los traductores automáticos basados en modelos estadísticos. El éxito de UniArab se cimienta en el modelo funcional de…

This paper describes a new method for cross-lingual textual entailment (CLTE) detection based on machine translation (MT). We use sub-segment translations from different MT systems available online as a source of cross-lingual knowledge. In this work we describe and evaluate…

Previous work on an interactive system aimed at helping non-expert users to enlarge the monolingual dictionaries of rule-based machine translation (MT) systems worked by discarding those inflection paradigms that cannot generate a set of inflected word forms validated by the…

When training hidden-Markov-model-based part-of-speech (PoS) taggers involved in machine translation systems in an unsupervised manner the use of target-language information has proven to give better results than the standard Baum-Welch algorithm. The target-language-driven training algorithm proceeds by translating every possible…