Методы адаптации

This paper describes our Statistical Ma- chine Translation systems for the WMT10 evaluation, where LIMSI participated for two language pairs (French-English and German-English, in both directions). For German-English, we concentrated …...

Many effective adaptation techniques for statistical machine translation crucially rely on in-domain development sets to learn model parameters. In this paper we present a novel method that automatically generates the …...

AbstractThe training data for statistical machine translation are gathered from various sources representing a mixture of domains. In this work, we argue that when translating dialects representing varieties of the …...

This paper gives a detailed experiment feed- back of different approaches to adapt a sta- tistical machine translation system towards a targeted translation project, using only small amounts of parallel …...

AbstractMassively multilingual language models such as multilingual BERT offer state-of-the-art cross-lingual transfer performance on a range of NLP tasks. However, due to limited capacity and large differences in pretraining data …...