Successful Research Year for CAMeL

2019 Lab Achievements


A successful research year for the Computational Approaches to Modeling Language Lab (CAMeL) at NYUAD

Researchers and students in the Computational Approaches to Modeling Language lab (CAMeL) at New York University Abu Dhabi have published 14 papers and released four resources in 2019 in the field of natural language processing.  Some of the papers were presented at the following conferences: NAACL 2019 (Minneapolis, USA), ACL 2019 (Florence, Italy), MT Summit 2019 (Dublin, Ireland), Interspeech 2019 (Graz, Austria), and EMNLP 2019 (Hong Kong, China).  Some of these efforts were in collaboration with researchers from other institutions including American University of Beirut, Carnegie Mellon University Qatar, Columbia University, Element AI, Google, Ohio State University, and the Qatar Computing Research Institute.

The CAMeL Lab research areas include developing new artificial intelligence algorithms for language processing, creating resources and tools to support research in computational linguistics, as well as creating new annotation standards and guidelines with a focus on the Arabic language and its dialects.

Publications by Theme

Computational Morphology
Dialect Identification
Information Extraction
Machine Translation
Sentiment Analysis
Other

Speech Evaluation

  • Towards Variability Resistant Dialectal Speech Evaluation by Ahmed Ali, Salam Khalifa, and Nizar Habash. (Interspeech 2019).

Gender Bias in AI

Resources

Tools
Corpora
  • The Margarita Dialogue Corpus - A collection of out-of-context and in-context question-answer pairs for developing time-offset interaction dialogue systems.