@article{TACL1290,
	author = {Jin, Lifeng  and Doshi-Velez, Finale  and Miller, Timothy  and Schuler, William  and Schwartz, Lane },
	title = {Unsupervised Grammar Induction with Depth-bounded PCFG},
	journal = {Transactions of the Association for Computational Linguistics},
	volume = {6},
	year = {2018},
	keywords = {},
	abstract = {There has been recent interest in applying cognitively or empirically motivated bounds on recursion depth to limit the search space of grammar induction models (Ponvert et al., 2011; Noji and Johnson, 2016; Shain et al., 2016). This work extends this depth-bounding approach to probabilistic context-free grammar induction (DB-PCFG), which has a smaller parameter space than hierarchical sequence models, and therefore more fully exploits the space reductions of depth-bounding. Results for this model on grammar acquisition from transcribed child-directed speech and newswire text exceed or are competitive with those of other models when evaluated on parse accuracy. Moreover, grammars acquired from this model demonstrate a consistent use of category labels, something which has not been demonstrated by other acquisition models. },
	issn = {2307-387X},
	url = {https://www.transacl.org/ojs/index.php/tacl/article/view/1290},
	pages = {211--224}
}