Interleaving natural language parsing and generation through uniform processing
Artificial Intelligence
Journal of the ACM (JACM)
An efficient context-free parsing algorithm
Communications of the ACM
Stochastic inversion transduction grammars and bilingual parsing of parallel corpora
Computational Linguistics
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
A uniform architecture for parsing and generation
COLING '88 Proceedings of the 12th conference on Computational linguistics - Volume 2
Learning Chinese bracketing knowledge based on a bilingual language model
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Multitext Grammars and synchronous parsers
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Loosely tree-based alignment for 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
Experiments in parallel-text based grammar induction
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Statistical machine translation by parsing
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
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We present an Earley-style dynamic programming algorithm for parsing sentence pairs from a parallel corpus simultaneously, building up two phrase structure trees and a correspondence mapping between the nodes. The intended use of the algorithm is in bootstrapping grammars for less studied languages by using implicit grammatical information in parallel corpora. Therefore, we presuppose a given (statistical) word alignment underlying in the synchronous parsing task; this leads to a significant reduction of the parsing complexity. The theoretical complexity results are corroborated by a quantitative evaluation in which we ran an implementation of the algorithm on a suite of test sentences from the Europarl parallel corpus.