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Translational equivalence in Statistical Machine Translation or meaning as co-occurrence
2021
Linguistica Antverpiensia, New Series – Themes in Translation Studies
In this paper, we will describe the current state-of-the-art of Statistical Machine Translation (SMT), and reflect on how SMT handles meaning. Statistical Machine Translation is a corpus-based approach to MT: it de-rives the required knowledge to generate new translations from corpora. General-purpose SMT systems do not use any formal semantic representa-tion. Instead, they directly extract translationally equivalent words or word sequences – expressions with the same meaning – from bilingual
doi:10.52034/lanstts.v7i.215
fatcat:bit5hp4c3rgnlpa7gncew42gtq