Bayesian grammar induction for language modeling

Bayesian grammar induction for language modeling (1995)

by Stanley F. Chen

Venue:	In Proceedings of ACL
Citations:	49 - 2 self

Datum	Value	Source
TITLE	Bayesian grammar induction for language modeling	INFERENCE
AUTHOR NAME	Stanley F. Chen	SVM HeaderParse 0.2
AUTHOR AFFIL	Aiken Computation Laboratory; Division of Applied Sciences; Harvard University	SVM HeaderParse 0.2
AUTHOR ADDR	Cambridge, MA 02138	SVM HeaderParse 0.2
ABSTRACT	We describe a corpus-based induction algorithm for probabilistic context-free grammars. The algorithm employs a greedy heuristic search within a Bayesian framework, and a post-pass using the Inside-Outside algorithm. We compare the performance of our algorithm to n-gram models and the Inside-Outside algorithm in three language modeling tasks. In two of the tasks, the training data is generated by a probabilistic context-free grammar and in both tasks our algorithm outperforms the other techniques. The third task involves naturally-occurring data, and in this task our algorithm does not perform as well as n-gram models but vastly outperforms the Inside-Outside algorithm. 1	SVM HeaderParse 0.2
YEAR	1995	INFERENCE
VENUE	In Proceedings of ACL	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
CITATIONS	21 found	ParsCit 1.0