Abstract. We propose a novel pipeline for translation into morphologically rich languages which consists of two steps: initially, the source string is ...

Machine Translation with Source-Predicted Target. Morphology. In Y. Al-Onaizan, & W. Lewis (Eds.), Proceedings of MT Summit XV. - Vol. 1: MT. Researchers ...

As a proof of concept we first show improved translation performance for a phrase-based model translating source strings enriched with morphological features ...

Apr 3, 2024 · Morphological modeling in neural machine translation (NMT) is a promising approach to achieving open-vocabulary machine translation.

Sep 29, 2017 · Abstract. This paper describes a two-step machine translation system that addresses the issue of translating into a morphologically.

End-to-end training makes the neural ma- chine translation (NMT) architecture sim- pler, yet elegant compared to traditional statistical machine translation ...

We improve the quality of statistical machine translation (SMT) by applying models that predict word forms from their stems using extensive morphological ...

Rule-based machine translation (RBMT) methods use bilingual dictionaries and manually written rules to translate source language texts into target language ...

Morpheme – the smallest unit of language that carries information about meaning or function. • Word – the smallest free form in language.

This work applies inflection generation models in translating English into two morphologically complex languages, Russian and Arabic, and shows that the ...