How can computational linguistics inform linguistic theory?
I am a computational linguist using data science to model both the emergence of grammatical structure and variation in grammatical structure using large multi-lingual corpora. My recent work has also focused on the impact of linguistic variation on computational models and on low-resource contexts. I have published over 30 papers and my first book was recently published by Cambridge University Press. My interdisciplinary teaching experience includes a MOOC which has now taught over 11,000 students about natural language processing.
- Dunn J. (2022) Natural Language Processing for Corpus Linguistics. Cambridge University Press. http://dx.doi.org/10.1017/9781009070447.
- Dunn J. (2022) Cognitive Linguistics Meets Computational Linguistics: Construction Grammar, Dialectology, and Linguistic Diversity.. In Tay D; Pan MX (Ed.), Data Analytics in Cognitive Linguistics: Methods and Insights: 273-308.De Gruyter Mouton. http://dx.doi.org/10.1515/9783110687279-010.
- Dunn J. and Nijhof W. (2022) Language Identification for Austronesian Languages. In Proceedings of the 13th International Conference on Language Resources and Evaluation: 6530-6539. European Language Resources Association.
- Dunn J. and Wong S. (2022) Stability of Syntactic Dialect Classification Over Space and Time. In Proceedings of the International Conference on Computational Linguistics: 26-36.
- Dunn J., Li H. and Sastre D. (2022) Predicting Embedding Reliability in Low-Resource Settings Using Corpus Similarity Measures. In Proceedings of the 13th International Conference on Language Resources and Evaluation: 6461-6470. European Language Resources Association.