Бірлескен ықтималдық моделі

. We propose a phrase-based context-dependent joint probability model for Named Entity (NE) translation. Our proposed model consists of a lexical mapping model and a permutation model. Target phrases are …...

AbstractThe Joint Probability Model proposed by Marcu and Wong (2002) provides a probabilistic framework for modeling phrase-based statistical machine transla- tion (SMT). The model’s usefulness is, however, limited by the …...

We present a novel approach to integrate transliteration into Hindi-to-Urdu statisti- cal machine translation. We propose two probabilistic models, based on conditional and joint probability formulations, that are novel solutions …...