Automatic learning of parallel dependency treelet pairs

Authors:
Yuan Ding;Martha Palmer
Affiliations:
Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA;Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA
Venue:
IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
Year:
2004

Citing 13
Cited 4

A statistical approach to machine translation

Computational Linguistics
Machine translation divergences: a formal description and proposed solution

Computational Linguistics
Automatic grammar generation from two different perspectives

Automatic grammar generation from two different perspectives
Learning dependency translation models as collections of finite-state head transducers

Computational Linguistics - Special issue on finite-state methods in NLP
The mathematics of statistical machine translation: parameter estimation

Computational Linguistics - Special issue on using large corpora: II
Stochastic inversion transduction grammars and bilingual parsing of parallel corpora

Computational Linguistics
Synchronous tree-adjoining grammars

COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 3
A syntax-based statistical translation model

ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
A decoder for syntax-based statistical MT

ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Loosely tree-based alignment for machine translation

ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Minimum error rate training in statistical machine translation

ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Phrasal cohesion and statistical machine translation

EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Design of a multi-lingual, parallel-processing statistical parsing engine

HLT '02 Proceedings of the second international conference on Human Language Technology Research

Dependency treelet translation: syntactically informed phrasal SMT

ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Machine translation using probabilistic synchronous dependency insertion grammars

ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Chinese-Japanese clause alignment

CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
Mining rules for rewriting states in a transition-based dependency parser

PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

Induction of synchronous grammars from empirical data has long been an unsolved problem; despite generative synchronous grammars theoretically suit the machine translation task very well. This fact is mainly due to pervasive structural divergences between languages. This paper presents a statistical approach that learns dependency structure mappings from parallel corpora. The new algorithm automatically learns parallel dependency treelet pairs from loosely matched non-isomorphic dependency trees while keeping computational complexity polynomial in the length of the sentences. A set of heuristics is introduced and specifically optimized for parallel treelet learning purposes using Minimum Error Rate training.