(Apologies for cross-posting)

Dear Colleagues,

We are pleased to announce that the submission is open for a new research topic 
in   Frontiers in Artificial Intelligence -  Natural Language Processing for 
Low-resource Languages and Domains.

Deadlines:
Abstract submission: 01 March 2022
Manuscript submission: 01 May 2022

We welcome any type of contributions related to low resource languages and 
domains. These include, but are not limited to:

  *   NLP Techniques for low-resource languages or domains
     *   Domain adaptation
     *   Transfer learning
     *   Zero-shot and few-shot learning
     *   Meta learning
     *   Knowledge distillation
     *   Multilingual and cross-lingual learning
     *   Data augmentation
  *   Dataset and Evaluation for low-resource languages or domains
     *   New benchmarks
     *   Evaluation Mechanism
     *   Multimodal resources Language resources (multilingual/monolingual, 
annotated/unannotated)
  *   NLP Tasks for low-resource languages or domains
     *   Bias, fairness and ethics in NLP
     *   Dialog and interactive systems
     *   Discourse and pragmatics
     *   Document analysis including text categorization, topic models, and 
retrieval
     *   Natural language generation
     *   Information extraction, text mining, and question answering
     *   Language-inclusive multimodal integration
     *   Machine translation
     *   Multilinguality
     *   Phonology, morphology, and word segmentation
     *   Semantics
     *   Text classification
     *   Fake news and hate-speech detection
     *   Sentiment analysis and opinion mining
     *   Social media analysis: Twitter, blogs, discussion forums, and other 
social media
     *   Speech, prosody, and spoken dialog
     *   Summarization
     *   Tagging, chunking, syntax, and parsing

For more information, visit 
https://www.frontiersin.org/research-topics/28809/natural-language-processing-for-low-resource-languages-and-domains

Regards,
The topic editors
Matthew Purver, Surangika Ranathunga, Ravi Shekhar, Rishemjit Kaur, En-Shiun 
Annie Lee

--
Ravi Shekhar
EECS, QMUL
http://shekharravi.github.io



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