English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

In this research paper, I will elaborate on a method to evaluate machinetranslation models based on their performance on underlying syntacticalphenomena between English and Arabic languages. This method is especiallyimportant as such "neural" and "machine learning" are hard to fine-tune andchange. Thus, finding a way to evaluate them easily and diversely would greatlyhelp the task of bettering them.

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