Algorithms for Weighted Pushdown Automata

Alexandra Butoi, Brian DuSell, Tim Vieira, Ryan Cotterell, David Chiang


Abstract
Weighted pushdown automata (WPDAs) are at the core of many natural language processing tasks, like syntax-based statistical machine translation and transition-based dependency parsing. As most existing dynamic programming algorithms are designed for context-free grammars (CFGs), algorithms for PDAs often resort to a PDA-to-CFG conversion. In this paper, we develop novel algorithms that operate directly on WPDAs. Our algorithms are inspired by Lang’s algorithm, but use a more general definition of pushdown automaton and either reduce the space requirements by a factor of |Gamma| (the size of the stack alphabet) or reduce the runtime by a factor of more than |Q| (the number of states). When run on the same class of PDAs as Lang’s algorithm, our algorithm is both more space-efficient by a factor of |Gamma| and more time-efficient by a factor of |Q| x |Gamma|.
Anthology ID:
2022.emnlp-main.656
Volume:
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates
Editors:
Yoav Goldberg, Zornitsa Kozareva, Yue Zhang
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
9669–9680
Language:
URL:
https://aclanthology.org/2022.emnlp-main.656
DOI:
10.18653/v1/2022.emnlp-main.656
Bibkey:
Cite (ACL):
Alexandra Butoi, Brian DuSell, Tim Vieira, Ryan Cotterell, and David Chiang. 2022. Algorithms for Weighted Pushdown Automata. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 9669–9680, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
Cite (Informal):
Algorithms for Weighted Pushdown Automata (Butoi et al., EMNLP 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.emnlp-main.656.pdf