Syntax-based reordering model for phrasal statistical machine translation

To deal with the long-distance reordering, a linguistically syntax-based reordering model was presented for phrasal statistical machine translation. In this model, the syntax structure was decomposed according to the phrase segmentation to avoid the inconsistence between phrase and syntax. The reord...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Tongxin Xuebao S. 7 - 14
Hauptverfasser:	XUE Yong-zeng, LI Sheng, ZHAO Tie-jun, YANG Mu-yun
Format:	Journal Article
Sprache:	Chinesisch
Veröffentlicht:	Editorial Department of Journal on Communications 01.01.2008
Schlagworte:	artificial intelligence phrase statistical translation model syntax-based reordering
ISSN:	1000-436X
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Beschreibung
Zusammenfassung:	To deal with the long-distance reordering, a linguistically syntax-based reordering model was presented for phrasal statistical machine translation. In this model, the syntax structure was decomposed according to the phrase segmentation to avoid the inconsistence between phrase and syntax. The reordering sequence of the sub-structures of a parse tree was decided by the word and phrase alignments. The reordering probability of the sub-structure was calculated on the reordering probabilities of the inside nodes, which was defined as a feature function of the log-linear statistical translation model. Experimental results show that the BLEU scores of the translation results were significantly improved compared with a conventional statistical phrase-based model. Therefore, it is effective to introduce the linguistic syntax for phrase reordering. The presented reordering model is able to efficiently incorporate the syntax into the translation process of phrases.
ISSN:	1000-436X