Katharina Kann

Postdoctoral Research Associate · New York University · kann@nyu.edu · CV

Universal Natural Language Processing: How can we build natural language processing systems that work for all of the world’s languages?

While an enormous amount of time, effort, and resources has been invested into developing technology for English, other languages are often overlooked. I am convinced that, in order to make NLP technologies accessible and useful for a wider and more diverse variety of users, more emphasis should be put on developing models for languages besides English, including low-resource languages. Thus, an important goal of my research is to develop computational approaches which perform well across a large variety of languages which might differ from English in their typology as well as the amount of available resources.

Deep Learning · Low-Resource Languages · Transfer Learning · Morphology


Publications

2020
  • Katharina Kann. Acquisition of Inflectional Morphology in Artificial Neural Networks With Prior Knowledge. In Proceedings of the Meeting of the Society for Computation in Linguistics, New Orleans, USA, January 2020 (to appear).

2019
  • Johannes Bjerva, Katharina Kann and Isabelle Augenstein. Transductive Auxiliary Task Self-Training for Neural Multi-Task Models. In Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource Natural Language Processing, Hong Kong, China, November 2019 (to appear).

  • Katharina Kann, Anhad Mohananey, Kyunghyun Cho and Samuel R. Bowman. Neural Unsupervised Parsing Beyond English. In Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource Natural Language Processing, Hong Kong, China, November 2019 (to appear).

  • Katharina Kann, Kyunghyun Cho and Samuel R. Bowman. Towards Realistic Practices In Low-Resource Natural Language Processing: The Development Set. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Hong Kong, China, November 2019 (to appear).

  • Yadollah Yaghoobzadeh, Katharina Kann, T. J. Hazen, Eneko Agirre and Hinrich Schütze. Probing for Semantic Classes: Diagnosing the Meaning Content of Word Embeddings. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, Florence, Italy, August 2019.

  • Manuel Mager, Özlem Çetinoğlu and Katharina Kann. Subword-Level Language Identification for Intra-Word Code-Switching. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics, Minneapolis, USA, June 2019.

  • Katharina Kann*, Alex Warstadt*, Adina Williams* and Samuel R. Bowman. Verb Argument Structure Alternations in Word and Sentence Embeddings. In Proceedings of the Meeting of the Society for Computation in Linguistics, New York, USA, January 2019.

2018
  • Ryan Cotterell, Christo Kirov, John Sylak-Glassman, Géraldine Walther, Ekaterina Vylomova, Arya D. McCarthy, Katharina Kann, Sebastian Mielke, Garrett Nicolai, Miikka Silfverberg, David Yarowsky, Jason Eisner and Mans Hulden. The CoNLL--SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection. In Proceedings of the SIGNLL Conference on Computational Natural Language Learning, Brussels, Belgium, October/November 2018.

  • Katharina Kann, Stanislas Lauly and Kyunghyun Cho. The NYU System for the CoNLL-SIGMORPHON 2018 Shared Task on Universal Morphological Reinflection. In Proceedings of the CoNLL-SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection, Brussels, Belgium, October/November 2018.

  • Katharina Kann and Hinrich Schütze. Neural Transductive Learning and Beyond: Morphological Generation in the Minimal-Resource Setting. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October/November 2018.

  • Katharina Kann, Sascha Rothe and Katja Filippova. Sentence-Level Fluency Evaluation: References Help, But Can Be Spared! In Proceedings of the SIGNLL Conference on Computational Natural Language Learning, Brussels, Belgium, October/November 2018.

  • Manuel Mager, Elisabeth Mager, Alfonso Medina-Urrea, Ivan Meza and Katharina Kann. Lost in Translation: Analysis of Information Loss During Machine Translation Between Polysynthetic and Fusional Languages. In Proceedings of All Together Now? Computational Modeling of Polysynthetic Languages, Santa Fe, USA, August 2018.

  • Katharina Kann, Johannes Bjerva, Isabelle Augenstein, Barbara Plank and Anders Søgaard. Character-level Supervision for Low-resource POS Tagging. In Proceedings of the 1st Workshop on Deep Learning Approaches for Low-Resource Natural Language Processing, Melbourne, Australia, July 2018.

  • Yadollah Yaghoobzadeh, Katharina Kann and Hinrich Schütze. Evaluating Word Embeddings in Multi-label Classification Using Fine-grained Name Typing. In Proceedings of the 3rd Workshop on Representation Learning for NLP, Melbourne, Australia, July 2018.

  • Katharina Kann*, Jesus Manuel Mager Hois*, Ivan Vladimir Meza Ruiz and Hinrich Schütze. Fortification of Neural Morphological Segmentation Models for Polysynthetic Minimal-Resource Languages. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies New Orleans, USA, June 2018. pdf bib

2017
  • Katharina Kann and Hinrich Schütze. Unlabeled Data for Morphological Generation With Character-Based Sequence-to-Sequence Models. In Proceedings of the 1st Workshop on Subword and Character Level Models in NLP, Copenhagen, Denmark, September 2017. pdf bib

  • Huiming Jin and Katharina Kann. Exploring Cross-Lingual Transfer of Morphological Knowledge In Sequence-to-Sequence Models. In Proceedings of the 1st Workshop on Subword and Character Level Models in NLP, Copenhagen, Denmark, September 2017. pdf bib

  • Katharina Kann and Hinrich Schütze. The LMU System for the CoNLL-SIGMORPHON 2017 Shared Task on Universal Morphological Reinflection. In Proceedings of the CoNLL-SIGMORPHON 2017 Shared Task: Universal Morphological Reinflection, Vancouver, Canada, August 2017. pdf bib

  • Toms Bergmanis, Katharina Kann, Hinrich Schütze and Sharon Goldwater. Training Data Augmentation for Low-Resource Morphological Inflection. In Proceedings of the CoNLL-SIGMORPHON 2017 Shared Task: Universal Morphological Reinflection, Vancouver, Canada, August 2017. pdf bib

  • Katharina Kann, Ryan Cotterell and Hinrich Schütze. One-Shot Neural Cross-Lingual Transfer for Paradigm Completion. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, Vancouver, Canada, August 2017. pdf bib

  • Katharina Kann, Ryan Cotterell and Hinrich Schütze. Neural Multi-Source Morphological Reinflection. In Proceedings of the 2017 Conference of the European Chapter of the Association for Computational Linguistics, Valencia, Spain, April 2017. pdf bib

2016
  • Katharina Kann, Ryan Cotterell and Hinrich Schütze. Neural Morphological Analysis: Encoding-Decoding Canonical Segments. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, Austin, USA, November 2016. pdf bib

  • Katharina Kann and Hinrich Schütze. MED: The LMU System for the SIGMORPHON 2016 Shared Task on Morphological Reinflection. In Proceedings of the 14th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology, Berlin, Germany, August 2016. pdf bib

  • Katharina Kann and Hinrich Schütze. Single-Model Encoder-Decoder with Explicit Morphological Representation for Reinflection. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, Berlin, Germany, August 2016. pdf bib

Travels

Philadelphia, USA · October 2019 · CLunch



Ann Arbor, USA · October 2019 · Michigan AI Symposium



Guanajuato, Mexico · October 2019 · PLAGAA

Write Me

Please feel free to contact me if you are interested in my work or if you would like to work with me.