# Part of Speech and Universal Dependency effects on English Arabic Machine Translation

Authors: Ofek Rafaeli, Omri Abend, Leshem Choshen, Dmitry Nikolaev
Venue: CoRR (2021)

## Abstract
In this research paper, I will elaborate on a method to evaluate machine translation models based on their performance on underlying syntactical phenomena between English and Arabic languages. This method is especially important as such"neural"and"machine learning"are hard to fine-tune and change. Thus, finding a way to evaluate them easily and diversely would greatly help the task of bettering them.

## Links
- arXiv: https://arxiv.org/abs/2106.00745
- PDF: https://arxiv.org/pdf/2106.00745
- HTML: https://ar5iv.labs.arxiv.org/html/2106.00745
- Hugging Face: https://huggingface.co/papers/2106.00745
- alphaXiv: https://www.alphaxiv.org/abs/2106.00745
- Semantic Scholar: https://www.semanticscholar.org/paper/235293879

## How to cite
@article{DBLP:journals/corr/abs-2106-00745,
author       = {Ofek Rafaeli and
                  Omri Abend and
                  Leshem Choshen and
                  Dmitry Nikolaev},
  title        = {Part of Speech and Universal Dependency effects on English Arabic
                  Machine Translation},
  journal      = {CoRR},
  volume       = {abs/2106.00745},
  year         = {2021},
  url          = {https://arxiv.org/abs/2106.00745},
  eprinttype    = {arXiv},
  eprint       = {2106.00745},
  timestamp    = {Mon, 25 Oct 2021 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2106-00745.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}