- Grammar induction from (lots of) words alone. John K Pate, and Mark Johnson. In Proceedings of COLING 2016. [code]
- A computationally efficient algorithm for learning topical collocation models. Zhendong Zhao, Lan Du, Benjamin Boerschinger, John K Pate, and Mark Johnson. In Proceedings of ACL 2015.
- Topic segmentation in an ordering-based topic model. Lan Du, John K Pate, and Mark Johnson. In AAAI 2015.
- Talkers account for listener and channel characteristics to communicate efficiently. John K Pate and Sharon Goldwater. Journal of Memory and Language. 78. 1—17
- Topic Models with Topic Ordering Regularities for Topic Segmentation. Lan Du, John K Pate, and Mark Johnson. In Proceedings of the 2014 International Conference on Data Mining.
- Syllable weight encodes mostly the same information for English word segmentation as dictionary stress. John K Pate and Mark Johnson. In Proceedings of the Conference on Empirical Methods in Natural Language Processing.
- Children's perception of dialect variation. Laura Wagner, Cynthia Clopper, and John K Pate. Journal of Child Language. 41. 1062—1084.
- Unsupervised dependency parsing with acoustic cues. John K Pate and Sharon Goldwater. In Transactions of the Association for Computational Linguistics (TACL) 1. pp 63—74.
- Predictability effects in adult-directed and infant-directed speech: Does the listener matter? John K Pate and Sharon Goldwater. In Proceedings of the 33rd annual meeting of the Cognitive Science Society.
- Unsupervised syntactic chunking with acoustic cues: Computational models for prosodic bootstrapping. John K Pate and Sharon Goldwater (2011). In Proceedings of the 2nd Workshop on Cognitive Modeling and Computational Linguistics. [Best student paper award]
- Refining Syntactic Categories Using Local Contexts — Experiments in Unlexicalized PCFG Parsing. John Pate and Detmar Meurers (2007). In Proceedings of the Sixth International Workshop on Treebanks and Linguistic Theories.