281 citations · 902 across the 36 of their papers we have counts for
4 papers · 1 filter
Challenging Language-Dependent Segmentation for Arabic: An Application to Machine Translation and Part-of-Speech Tagging
Hassan Sajjad, Fahim Dalvi, Nadir Durrani +3
Word segmentation plays a pivotal role in improving any Arabic NLP application. Therefore, a lot of research has been spent in improving its accuracy. Off-the-shelf tools, however,…
Neural Machine Translation Training in a Multi-Domain Scenario
Hassan Sajjad, Nadir Durrani, Fahim Dalvi +2
In this paper, we explore alternative ways to train a neural machine translation system in a multi-domain scenario. We investigate data concatenation (with fine tuning), model stac…
What do Neural Machine Translation Models Learn about Morphology?
Yonatan Belinkov, Nadir Durrani, Fahim Dalvi +2
Neural machine translation (MT) models obtain state-of-the-art performance while maintaining a simple, end-to-end architecture. However, little is known about what these models lea…
QCRI Machine Translation Systems for IWSLT 16
Nadir Durrani, Fahim Dalvi, Hassan Sajjad +1
This paper describes QCRI's machine translation systems for the IWSLT 2016 evaluation campaign. We participated in the Arabic->English and English->Arabic tracks. We built both Phr…