Ensuring that the Arabic language flourishes in the digital world is a priority area of QCRI’s research. We are dedicated to promoting the Arabic language in the information age. Some of our current research projects address the challenges related to lack of content and equally important, extracting that content, analyzing and transforming it.
Our Arabic Language Technologies research department is a recognized world leader in the areas of speech recognition, machine translation and question answering.
Our focus areas include:
- - Fully automatic processing and annotating Arabic text including morphological analysis, parts-of-speech tagging, parsing, diacritization, named entity recognition, and spelling correction.
- - Arabic speech recognition of formal Arabic and dialectal Arabic, also dialect identification and speaker identification.
- - Machine translation, with focus on translation between Arabic and English. In combination with the speech recognition technology the application areas include translation of broadcast news and real-time translation of lectures.
- - Multilingual video search in large archives of broadcast news.
- - Optical character recognition for historic Arabic documents.
- - Question-answering systems for Arabic and English, which includes deep semantic processing of text, discourse analysis and dialog processing.
The ALT team has also worked on technology for education and on assistive technology, which has resulted in the development of apps - the Jalees Reader e-book reader and the BrailleEasy keyboard for blind and visually impaired people - both of which have been widely adopted.
The ALT department in 2014 organized one of the premier conferences in the field of natural language processing, the Conference on Empirical Methods in Natural Language Processing (EMNLP). Members of the group are frequently chairs of major conferences and workshops.
We have collaborated and continue to collaborate with a number of academic institutions and industry partners including MIT, CMU, Al Jazeera, Qatar Living, The Boeing Company, and stakeholders including the Supreme Council of Education, Sidra, and the Social and Cultural Center for the Blind.
ALT strives to keep a balance between world-class research and creating impactful technologies. On one hand this means having published more than 200 papers, on the other it has resulted in transferring technology through licensing or the creation of a startup company. Besides the aforementioned Jalees Reader and BrailleEasy, the following technologies have been commercialized: TweetMogaz (Tweet analysis platform), Farasa (the Arabic NLP toolkit) and QATS (QCRI advanced speech recognition).
Being part of a research institute in start-up mode, helping to build a strong team doing world class research, and at the same time experiencing a different environment in terms of culture and language, geography and climate.
In the Media
Map apps may have changed our world, but they still haven’t mapped all of it yet. Specifically, mapping roads can be difficult and tedious: even after taking aerial images, companies still have to ...
Perhaps you bought some illegal narcotics on the Silk Road half a decade ago, back when that digital black market for every contraband imaginable was still online and bustling. You might already ...
Each year, Qatar Computing Research Institute organizes a summer internship program for undergraduate students studying computer science, computer engineering and other disciplines. The internship is unpaid, and QCRI does not provide any visa support.
Artificial Intelligence for Oncology: Learning to Cure Cancer from Images and Text A talk by Professor Regina Barzilay, MIT CSAIL Winner of 2017 MacArthur ‘genius grant’ At Education City Student ...
Project to build defensive platform to detect emerging cyberattacks awarded $1.65m grant.
Meeting updates joint research projects between the two institutions and will feature 'genius grant' recipient Prof. Regina Barzilay, who uses AI to detect cancer, as keynote speaker.
Her Highness Sheikha Moza bint Nasser presents accolade for system that automatically converts speech to text using state-of-the-art speech recognition techniques.