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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 learn about source and… (More)
- Kareem Darwish, Hassan Sajjad, Hamdy Mubarak
- EMNLP
- 2014
Several recent papers on Arabic dialect identification have hinted that using a word unigram model is sufficient and effective for the task. However, most previous work was done on a standard fairly… (More)
While neural machine translation (NMT) models provide improved translation quality in an elegant, end-to-end framework, it is less clear what they learn about language. Recent work has started… (More)
The role of social media, in particular microblogging platforms such as Twitter, as a conduit for actionable and tactical information during disasters is increasingly acknowledged. However,… (More)
- Ahmed Abdelali, Francisco Guzmán, Hassan Sajjad, Stephan Vogel
- LREC
- 2014
This paper presents the AMARA corpus of on-line educational content: a new parallel corpus of educational video subtitles, multilingually aligned for 20 languages, i.e. 20 monolingual corpora and 190… (More)
- Nadir Durrani, Hassan Sajjad, Hieu T. Hoang, Philipp Koehn
- EACL
- 2014
We investigate three methods for integrating an unsupervised transliteration model into an end-to-end SMT system. We induce a transliteration model from parallel data and use it to translate OOV… (More)
We propose a novel model to automatically extract transliteration pairs from parallel corpora. Our model is efficient, language pair independent and mines transliteration pairs in a consistent… (More)
We propose a language-independent method for the automatic extraction of transliteration pairs from parallel corpora. In contrast to previous work, our method uses no form of supervision, and does… (More)
We present novel models for domain adaptation based on the neural network joint model (NNJM). Our models maximize the cross entropy by regularizing the loss function with respect to in-domain model.… (More)
- Muhammad Moeen Uddin, Muhammad Ali Imran, Hassan Sajjad
- ArXiv
- 2014
People use microblogging platforms like Twitter to involve with other users for a wide range of interests and practices. Twitter profiles run by different types of users such as humans, bots,… (More)