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C.L.: A non-contiguous tree sequence alignment-based model for statistical machine translation (2009)
| Content Provider | CiteSeerX |
|---|---|
| Author | Sun, Jun Tan, Min Zhang Chew Lim |
| Description | The tree sequence based translation model al-lows the violation of syntactic boundaries in a rule to capture non-syntactic phrases, where a tree sequence is a contiguous sequence of sub-trees. This paper goes further to present a trans-lation model based on non-contiguous tree se-quence alignment, where a non-contiguous tree sequence is a sequence of sub-trees and gaps. Compared with the contiguous tree sequence-based model, the proposed model can well han-dle non-contiguous phrases with any large gaps by means of non-contiguous tree sequence alignment. An algorithm targeting the non-contiguous constituent decoding is also proposed. Experimental results on the NIST MT-05 Chi-nese-English translation task show that the pro-posed model statistically significantly outper-forms the baseline systems. 1 |
| File Format | |
| Language | English |
| Publisher Date | 2009-01-01 |
| Publisher Institution | Association for Computational Linguistics |
| Access Restriction | Open |
| Subject Keyword | Syntactic Boundary Non-contiguous Constituent Decoding Non-contiguous Phrase Baseline System Tree Sequence Statistical Machine Translation Pro-posed Model Non-contiguous Tree Se-quence Alignment Contiguous Tree Sequence-based Model Non-contiguous Tree Sequence Alignment Non-contiguous Tree Sequence Alignment-based Model Trans-lation Model Translation Model Non-syntactic Phrase Contiguous Sequence Non-contiguous Tree Sequence Experimental Result Large Gap |
| Content Type | Text |
| Resource Type | Article |
