# Egyptian Arabic to English Statistical Machine Translation System for NIST OpenMT'2015

arXiv: https://arxiv.org/abs/1606.05759 · HTML: https://mlsanity.com/paper/1606.05759/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Jun 2016.

## Built on by (most cited first, 1 of 1)

- [OSN-MDAD: Machine Translation Dataset for Arabic Multi-Dialectal Conversations on Online Social Media](https://mlsanity.com/paper/2309.12137/) (2023)

## Abstract (arXiv)

The paper describes the Egyptian Arabic-to-English statistical machine translation (SMT) system that the QCRI-Columbia-NYUAD (QCN) group submitted to the NIST OpenMT'2015 competition. The competition focused on informal dialectal Arabic, as used in SMS, chat, and speech. Thus, our efforts focused on processing and standardizing Arabic, e.g., using tools such as 3arrib and MADAMIRA. We further trained a phrase-based SMT system using state-of-the-art features and components such as operation sequence model, class-based language model, sparse features, neural network joint model, genre-based hierarchically-interpolated language model, unsupervised transliteration mining, phrase-table merging, and hypothesis combination. Our system ranked second on all three genres.