Tuesday, November 13, 2007

Trees that can help

Speaker: Alok Parlikar

Title: (S (NP (NP Trees) (SBAR (WHNP that) (S (VP can)))) (VP help))

Summary:

For the past two months, I have been working with Alon Lavie and Stephan
Vogel, on Chinese and English parse-trees, to investigate answers to the
following questions:

(a) Can constituency information and word level alignments be used to
align nodes in trees of parallel sentences? How precisely matched
(in meaning) are the yields of these aligned nodes?
(b) Can the parse trees and word-level alignments be used for learning
reordering rules? If we use these rules to reorder source sentences,
can we do any better at translation?

The current results show that:

(a) - Node Alignments from hand-aligned data are very precise.
- Using automatic word-alignments to align nodes gives over 70%
precision and over 40% recall.
(b) Using a 10-best reordering of words in the source sentences, with
a "dumb" reordering strategy has shown a 0.005 improvement in BLEU
score.

I would like to talk about the approaches that we have taken here, and to
discuss about strategies for improving these results.