An Application of Probabilistic Grammars to Efficient Machne Translation

• Authors: Paweł Skórzewski
• Languages of publication: PL

Abstracts

PL

In this paper we present one of the algorithms used to parse probabilistic context-free grammars: the A* parsing algorithm, which is based on the A* graph search method. We show an example of application of the algorithm in an existing machine translation system. The existing CYK-based parser used in the Translatica system was modified by applying the A* parsing algorithm in order to examine the possibilities of improving its performance. This paper presents the results of applying the A* algorithm with different heuristic functions and their impact on the performance of the parser.

• Publisher: Uniwersytet im. Adama Mickiewicza w Poznaniu
• Journal: Investigationes Linguisticae
• Year: 2010
• Volume: 21
• Pages: 90-98

Dates

published

2010-09-15

Contributors

author

Paweł Skórzewski

• Faculty of Mathematics and Computer Science, Adam Mickiwicz University, Poland

References

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• Roark, B.: Probabilistic Top-Down Parsing and Language Modeling. Computational Linguistics 27, pp. 249-276 (2001)
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• Skórzewski, P.: Efektywny parsing je¸zyka naturalnego przy u˙zyciu gramatyk probabilistycznych (Efficient Natural Language Parsing Using Probabilistic Grammars). Master Thesis on Adam Mickiewicz University, Pozna´n (2010)
• Skórzewski, P.: Effective Natural Language Parsing With Probabilistic Grammars). In Proceedings of Computational Linguistics – Applications, pp. 175-178. Wisła (2010)

Identifiers

DOI

10.14746/il.2010.21.6