Paper: Forest-based Tree Sequence to String Translation Model

ACL ID P09-1020
Title Forest-based Tree Sequence to String Translation Model
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2009

This paper proposes a forest-based tree se- quence to string translation model for syntax- based statistical machine translation, which automatically learns tree sequence to string translation rules from word-aligned source- side-parsed bilingual texts. The proposed model leverages on the strengths of both tree sequence-based and forest-based translation models. Therefore, it can not only utilize forest structure that compactly encodes exponential number of parse trees but also capture non- syntactic translation equivalences with linguis- tically structured information through tree se- quence. This makes our model potentially more robust to parse errors and structure di- vergence. Experimental results on the NIST MT-2003 Chinese-English translation task show that our method sta...