Hierarchical phrase-based translation representations

Authors:
Gonzalo Iglesias;Cyril Allauzen;William Byrne;Adrià de Gispert;Michael Riley
Affiliations:
University of Cambridge, Cambridge, U. K.;Google Research, New York, NY;University of Cambridge, Cambridge, U. K.;University of Cambridge, Cambridge, U. K.;Google Research, New York, NY
Venue:
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Year:
2011

Citing 16
Cited 4

Semirings, automata, languages

Semirings, automata, languages
On the Difficulty of Some Shortest Path Problems

STACS '03 Proceedings of the 20th Annual Symposium on Theoretical Aspects of Computer Science
Minimum error rate training in statistical machine translation

ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
A weighted finite state transducer translation template model for statistical machine translation

Natural Language Engineering
Hierarchical Phrase-Based Translation

Computational Linguistics
Rule filtering by pattern for efficient hierarchical translation

EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Hierarchical phrase-based translation with weighted finite state transducers

NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Machine translation as lexicalized parsing with hooks

Parsing '05 Proceedings of the Ninth International Workshop on Parsing Technology
Handbook of Weighted Automata

Handbook of Weighted Automata
OpenFst: a general and efficient weighted finite-state transducer library

CIAA'07 Proceedings of the 12th international conference on Implementation and application of automata
Efficient incremental decoding for tree-to-string translation

EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Dual decomposition for parsing with non-projective head automata

EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Hierarchical phrase-based translation with weighted finite-state transducers and shallow-n grammars

Computational Linguistics
Filters for efficient composition of weighted finite-state transducers

CIAA'10 Proceedings of the 15th international conference on Implementation and application of automata
Exact decoding of syntactic translation models through Lagrangian relaxation

HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
HMM Word and Phrase Alignment for Statistical Machine Translation

IEEE Transactions on Audio, Speech, and Language Processing

Using categorial grammar to label translation rules

WMT '12 Proceedings of the Seventh Workshop on Statistical Machine Translation
A pushdown transducer extension for the openfst library

CIAA'12 Proceedings of the 17th international conference on Implementation and Application of Automata
N-gram posterior probability confidence measures for statistical machine translation: an empirical study

Machine Translation
A global model for concept-to-text generation

Journal of Artificial Intelligence Research

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper compares several translation representations for a synchronous context-free grammar parse including CFGs/hypergraphs, finite-state automata (FSA), and pushdown automata (PDA). The representation choice is shown to determine the form and complexity of target LM intersection and shortest-path algorithms that follow. Intersection, shortest path, FSA expansion and RTN replacement algorithms are presented for PDAs. Chinese-to-English translation experiments using HiFST and HiPDT, FSA and PDA-based decoders, are presented using admissible (or exact) search, possible for HiFST with compact SCFG rulesets and HiPDT with compact LMs. For large rulesets with large LMs, we introduce a two-pass search strategy which we then analyze in terms of search errors and translation performance.