A PDF of my dissertation, Learning Phonology with Sequence-to-Sequence Neural Networks, can be downloaded here. To view the software I used for most of the simulations in it, click here.
If you’re interested in any of my other research, you can browse through all of my papers and presentations below.
| Topic | Method | Model/Algorithm |
-
Learning Sour Grapes Harmony
- Prickett (2023). Poster for the 41st West Coast Conference on Formal Linguistics
- Prickett (2023). Paper for the Proceedings of the 2022 Annual Meeting on Phonology
- Prickett (2022). Poster for the 2022 Annual Meeting on Phonology
- Prickett (2021). Poster for the 39th West Coast Conference on Formal Linguistics
-
Probabilistic Feature Attention as an alternative to variables
(Click here
to view the software used in this project)
- Prickett (2023). Paper in Linguistic Inquiry 54 (2), 219–249 (Manuscript)
- Prickett (2020). Presentation for the LSA's 2020 annual meeting
- Prickett (2019). Handout for the 2019 UNC Spring Colloquium
- Prickett (2018). Presentation for the Northeast Computational Phonology Circle
-
Boomerang Constraints: A Mechanism for Capturing Duke-of-York in Harmonic Serialism
- Prickett (2022). Poster for the 29th Manchester Phonology Meeting
-
Learning Stress Patterns with a Sequence-to-Sequence Neural Network
(Click here
to view the software used in this project)
- Prickett, Brandon and Joe Pater (2022). Paper for the Proceedings of the 2022 meeting of The Society for Computation in Linguistics
- Prickett, Brandon and Joe Pater (2022). Presentation for the 2022 meeting of The Society for Computation in Linguistics
-
Learning hidden structure with a Maximum Entropy Grammar
(Click here
to view the software used in this project)
- Pater, Joe and Brandon Prickett (2022). Paper in the Proceedings of the 2021 Annual Meeting on Phonology
- Pater, Joe and Brandon Prickett (2021). Poster for the 2021 Annual Meeting on Phonology
- Prickett, Brandon and Joe Pater (2019). Presentation for the 27th Manchester Phonology Meeting
-
Learning reduplication with a neural network that lacks explicit variables
(Click here to view the software used in this project)
- Prickett, Brandon, Aaron Traylor, and Joe Pater (2022). Paper in Journal of Language Modelling, 10(1), 1–38
- Prickett, Brandon, Aaron Traylor, and Joe Pater (2018). Paper in the Proceedings of the 15th SIGMORPHON workshop
- Prickett, Brandon, Aaron Traylor, and Joe Pater (2018). Poster presented at the 15th SIGMORPHON workshop
-
Modelling a subregular bias in phonological learning with Recurrent Neural Networks
- Prickett (2021). Paper in the Journal of Language Modelling, 9(1)
- Capturing phonotactic learning biases with a simple RNN
- Modeling the acquisition of phonological interactions: biases and generalization (Click here and here to view the software used in this project)
-
Learning reduplication, but not syllable reversal
- Prickett, Brandon, Elliott Moreton, Katya Pertsova, Joshua Fennell, Joe Pater, and Lisa Sanders (2021). Paper in the Proceedings of the 2020 Annual Meeting on Phonology
- Prickett, Brandon, Elliott Moreton, Katya Pertsova, Joshua Fennell, Joe Pater, and Lisa Sanders (2020). Poster for the 2020 Annual Meeting on Phonology
- Variables must be limited to a single feature
-
Learning biases in opaque interactions
(Click here to view the neural network and
here to view the EDL-based learner used in this project)
- Prickett (2019). Paper in Phonology, 36(4), 627-653 (Manuscript)
- Prickett (2018). Poster for LabPhon 16
- Prickett (2017). Presentation for the Northeast Computational Phonology Circle
-
Probing RNN encoder-decoder generalization of subregular functions using reduplication
- Nelson, Max, Hossep Dolatian, Jon Rawski, and Brandon Prickett (2020). Paper for the Proceedings of the 2020 meeting of The Society for Computation in Linguistics
- Nelson, Max, Hossep Dolatian, Jon Rawski, and Brandon Prickett (2020). Presentation for the 2020 meeting of The Society for Computation in Linguistics
-
Learning syntactic parameters without triggers by assigning credit and blame
- Prickett, Brandon, Kaden Holladay, Shay Hucklebridge, Max Nelson, Rajesh Bhatt, Gaja Jarosz, Kyle Johnson, Aleksei Nazarov, and Joe Pater (2019). Paper in the Proceedings of the 55th annual meeting of the Chicago Linguistics Society
- Prickett, Brandon, Kaden Holladay, Shay Hucklebridge, Max Nelson, Rajesh Bhatt, Gaja Jarosz, Kyle Johnson, Aleksei Nazarov, and Joe Pater (2019). Presentation for the 55th annual meeting of the Chicago Linguistics Society
-
Learning exceptionality and variation with lexically scaled MaxEnt
(Click here to view the software used in this project)
- Hughto, Coral, Andrew Lamont, Brandon Prickett, and Gaja Jarosz (2019). Paper in the Proceedings of the 2019 meeting of The Society for Computation in Linguistics
- Similarity-based phonological generalization
- Complexity and naturalness biases in phonotactics: Hayes and White (2013) revisited
-
Post-nasal devoicing as opacity: a problem for natural constraints
- Prickett (2017). Paper in the Proceedings of the 35th Annual Meeting of the West Coast Conference on Formal Linguistics
- Prickett (2017). Presentation for the 35th Annual Meeting of the West Coast Conference on Formal Linguistics
-
Emergent positional faithfulness in novel English blends
- Moreton, Elliott, Jennifer L. Smith, Katya Pertsova, Rachel Broad, and Brandon Prickett (2017). Paper in Language, 93(2), 347-380 (Manuscript)
- Broad, Rachel, Brandon Prickett, Elliott Moreton, Katya Pertsova, and Jennifer L. Smith (2015). Paper in the Proceedings of the 33rd Annual Meeting of the West Coast Conference on Formal Linguistics
-
Complexity and naturalness in first language and second language phonotactic learning
- Prickett (2015). MA Thesis, University of North Carolina at Chapel Hill
-
The Natchez fort at Sicily Island, Louisiana
- Steponaitis, Vin and Brandon Prickett (2014). Paper in Louisiana Archaeology, No. 41