Compounded words are a challenge for NLP applications such as machine translation (MT). We introduce methods to learn splitting rules from monolingual and parallel corpora. We eva...
Word and n-gram posterior probabilities estimated on N-best hypotheses have been used to improve the performance of statistical machine translation (SMT) in a rescoring framework....
Machine translation of human languages is a field almost as old as computers themselves. Recent approaches to this challenging problem aim at learning translation knowledge automat...
Recently, there has been an emphasis on creating shared resources for natural language processing applications. This has resulted in the development of high-quality tools and data...
We address the problem of simplifying Portuguese texts at the sentence level treating it as a "translation task". We use the Statistical Machine Translation (SMT) framewo...