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Maria Barrett

I am a Danish post doc working at the University of Copenhagen in collaboration with the Alexandra Institute. I work on NLP for Danish. I also work at the intersection of human, behavioral data and NLP.
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Email mria.barrett [at]

Ongoing projects

Named entity recognition for Danish

code base and annotated corpus

Co-reference resolution for Danish

Ongoing or recent (co-)supervison

EEG for named entity recognition

MA project by Lukas Mutthenthaler

Fake news detection

PhD project by Terne Sasha Thorn

Part-of-speech tagging using grammatical errors

MA thesis by Shuting Huang

Towards automatic fluency detection on sentence readings

MA thesis by Søren Søbæk and Elena Haffmans

Abstract at the Scandinavian Workshop on Applied Eye Tracking 2018

Grants and awards

Villum International Postdoc 2020

Three years post doc funding at the IT-University of Copenhagen starting July 2020 with the project Modelling relations in text using human data.

Villum press release

2019 ELLIS PhD award

ELLIS press release

CoNLL 2018 Special best paper award

"Sequence classification with human attention."

2018 Facebook Global Literacy Challenge

With Anders Søgaard



Barrett, M.; Kementchedjhieva, Y.; Elazar, Y.; Elliott, D.; Søgaard, A. (2019). "Adversarial Removal of Demographic Attributes Revisited." In EMNLP-IJCNLP (pp.6329–6334).


Barrett, M.; Bingel, J.; Hollenstein, N.; Rei, M.; Søgaard, A. (2018). "Sequence classification with human attention." In The SIGNLL Conference on Computational Natural Language Learning (CoNLL) (pp. 302–312). Special best paper award

Bingel, J; Barrett, M.; Klerke, S. (2018). "Predicting misreadings from gaze in children with reading difficulties." In The 13th Workshop on Innovative Use of NLP for Building Educational Applications@NAACL (pp. 24–34).

Barrett, M.; Gonzalez-Garduño, A.; Frermann, L. & Søgaard, A. (2018). "Unsupervised induction of linguistic categories with records of reading, speaking, and writing." In The 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL) (pp. 2028–2038).


Barrett, M.; Keller, F. & Søgaard, A. (2016). "Cross-lingual transfer of correlations between parts of speech and gaze features." In The 26th International Conference on Computational Linguistics (COLING): Proceedings of COLING 2016: technical papers (pp. 1330-1339).

Bingel, J.; Barrett, M. & Søgaard, A. (2016) "Extracting token-level signals of syntactic processing from fMRI - with an application to PoS induction". In ACL (pp. 747–755).

Barrett, M., Bingel, J., Keller, F., Søgaard, A. (2016) "Weakly supervised Part-of-Speech Induction from Eye-tracking Data". In ACL (pp. 579–584).

Barrett, M., Agíc, Z., and Søgaard, A. (2015) "The Dundee Treebank". In Treebanks and Linguistic Theories (TLT14) (pp. 242–248). [resource]

Barrett, M., & Søgaard, A. (2015). "Using reading behavior to predict grammatical functions". In Proc. of Workshop on Cognitive Aspects of Computational Language Learning (CogACLL) @EMNLP(pp. 1–5).


Klerke, S., Castilho, S., Barrett, M., & Søgaard, A. (2015). "Reading metrics for estimating task efficiency with MT output". In Proc. of Workshop on Cognitive Aspects of Computational Language Learning (CogACLL) @EMNLP ( pp. 6–13).

Barrett, M., & Søgaard, A. (2015). "Reading behavior predicts syntactic categories". In CoNLL 2015, (pp. 345–249).


San Agustin, J., Skovsgaard, H., Møllenbach, E., Barrett, M., Tall, M., Hansen, D. W., & Hansen, J. P. (2010). "Evaluation of a low-cost open-source gaze tracker". In Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications (pp. 77-80). ACM

Barrett, M., Skovsgaard, H., & San Agustin, J. (2009). "Performance evaluation of a Low-Cost gaze tracker for eye typing". In Proceedings of Conference on Communication by Gaze Interaction. Lyngby, Denmark: COGAIN (pp. 13-17).

Recent Work Experience

2008 - Present

Post doc

University of Copenhagen in collaboration with the Alexandra Institute




University of Copenhagen

Title: Improving natural language processing with human data : Eye tracking and other data sources reflecting cognitive text processing.
Supervisor: Prof., Dr.Phil., PhD Anders Søgaard