Arabic Language Technologies

Fingerprint Dive into the research topics where Arabic Language Technologies is active. These topic labels come from the works of this organisation's members. Together they form a unique fingerprint.

Semantics Engineering & Materials Science
Syntactics Engineering & Materials Science
Classifiers Engineering & Materials Science
Neural networks Engineering & Materials Science
Linguistics Engineering & Materials Science
Labeling Engineering & Materials Science
Processing Engineering & Materials Science
Experiments Engineering & Materials Science

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Research Output 2000 2019

A Factorial Deep Markov Model for Unsupervised Disentangled Representation Learning from Speech

Khurana, S., Rayhan Joty, S., Ali, A. & Glass, J., 1 May 2019, 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 6540-6544 5 p. 8683131. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; vol. 2019-May).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Arabic community question answering

Nakov, P., Marques, L., Moschitti, A. & Mubarak, H., 1 Jan 2019, In : Natural Language Engineering. 25, 1, p. 5-41 37 p.

Research output: Contribution to journalArticle

Syntactics
Formal languages
Learning algorithms
community
Learning systems

A Structured Learning Approach with Neural Conditional Random Fields for Sleep Staging

Aggarwal, K., Khadanga, S., Rayhan Joty, S., Kazaglis, L. & Srivastava, J., 22 Jan 2019, Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018. Song, Y., Liu, B., Lee, K., Abe, N., Pu, C., Qiao, M., Ahmed, N., Kossmann, D., Saltz, J., Tang, J., He, J., Liu, H. & Hu, X. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 1318-1327 10 p. 8622286. (Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Sleep
Air
Recurrent neural networks
Convolution
Health