Sunflower : a BTG based shift reduce decoderIntroducer 宋林峰

Core idea• Decoding in linear time• Take the advance of LR decoding in LM score computing• With BTG constrain to constrain the searching space• Use moses’s idea and framework

– The idea of choose a phrase randomly– The idea of distortion limit

How to satisfy BTG constrain• We store three stacks in every Edge:

– Stackcur : stack for coverd spans– Stacklhs : stack for the left uncovered spans of current block– Stackrhs : stack for the right uncovered spans of current block

How to satisfy BTG constrain

• Decoding strategy– Every time we choose a part of uncoverd span EXT from top

instance of Stacklhs or Stackrhs named CUR• CUR must be adjacent to the top instance of Stackcur• Latter we shall improve there always be such one

– Push the remaining left part of EXT (if has) back to Stacklhs– Push the remaining right part of EXT(if has) back to Stackrhs

An example

Action Stacklhs Stackcur Stackrhs

∅ (0) (1,6)

Rshift (1,4) (0)(5) (6)

Lshift ∅ (0)(5)(1) (6)(2,4)

Rshift (2) (0)(5)(1)(3) (6)(4)

Rshift & Reduce (2) (0)(5)(1)(3,4) (6)

Lshift & Reduce ∅ (0,5) (6)

Rshift & Reduce ∅ (0,6) ∅

Prove• Theorem : Every time the top instance of Stacklhs or

Stackrhs , either of them is adjacent to the top instance of Stackcur

• Prove : – At the beginning stacklhs is empty , stackrhs contains just one

element that is adjacent – Suppose now it is a legal state under the theorem, we choose one

span that is adjacent– whenever we extract the middle, the rightmost part, the leftmost

part, it is surly a legal state

Tricks• Decoding failure under moses’s distortion limit

– Under the current state, if we can not extend the edge, we choose the top element of stacklhs

– We will prove that there is always exist such element

• Punctuation limit strategy– We will not extend a punctuation and its right part unless its left

part has been fully extended– other stategy : Incremental cube-pruning for translation joint?

Results

System Dev(nist02) Test(nist05)

Test(nist08)

Orignal bruin 0.2647

Moses (msd distortion) 0.2599

Sunflower (maxent distortion) 0.2584

Sunflower (msd distortion) 0.2662

Corpus: 23w FBIS, with case-sensitive BLEU evaluation

References• Yang Feng, Haitao Mi, Yang Liu, Qun Liu. 2010. An Efficient Shift-Reduce Decoding

Algorithm for Phrase-Based Machine Translation. In Proceedings of COLING 2010: Poster Volume, pages 285-293, Beijing, China, August.

• Deyi Xiong, Qun Liu, and Shouxun Lin. Maximum Entropy Based Phrase Reordering Model for Statistical Machine Translation. In Proceedings of COLING-ACL 2006, Sydney, Australia.

Thank you