Index of papers in Proc. ACL 2010 that mention
  • BLEU points
Mi, Haitao and Liu, Qun
Abstract
Medium-scale experiments show an absolute and statistically significant improvement of +0.7 BLEU points over a state-of-the-art forest-based tree-to-string system even with fewer rules.
Experiments
As shown in the third line in the column of BLEU score, the performance drops 1.7 BLEU points over baseline system due to the poorer rule coverage.
Experiments
This suggests that using dependency language model really improves the translation quality by less than 1 BLEU point .
Experiments
With the help of the dependency language model, our new model achieves a significant improvement of +0.7 BLEU points over the forest 625 baseline system (p < 0.05, using the sign-test suggested by
Introduction
Medium data experiments (Section 5) show a statistically significant improvement of +0.7 BLEU points over a state-of-the-art forest-based tree-to-string system even with less translation rules, this is also the first time that a tree-to-tree model can surpass tree-to-string counterparts.
Model
(2009), their forest-based constituency-to-constituency system achieves a comparable performance against Moses (Koehn et al., 2007), but a significant improvement of +3.6 BLEU points over the 1-best tree-based constituency-to-constituency system.
BLEU points is mentioned in 7 sentences in this paper.
Topics mentioned in this paper:
Durrani, Nadir and Sajjad, Hassan and Fraser, Alexander and Schmid, Helmut
Evaluation
Both our systems (Model-1 and Model-2) beat the baseline phrase-based system with a BLEU point difference of 4.30 and 2.75 respectively.
Evaluation
The difference of 2.35 BLEU points between M1 and Pbl indicates that transliteration is useful for more than only translating OOV words for language pairs like Hindi-Urdu.
Final Results
BLEU point improvement and combined with all the heuristics (M2H123) gives an overall gain of 1.95 BLEU points and is close to our best results (M1H12).
BLEU points is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Xiao, Tong and Zhu, Jingbo and Zhu, Muhua and Wang, Huizhen
Background
For the phrase-based system, it yields over 0.6 BLEU point gains just after the 3rd iteration on all the data sets.
Background
Also as shown in Table 1, over 0.7 BLEU point gains are obtained on the phrase-based system after 10 iterations.
Background
The largest BLEU improvement on the phrase-based system is over 1 BLEU point in most cases.
BLEU points is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Yeniterzi, Reyyan and Oflazer, Kemal
Experimental Setup and Results
While N0un+Adj transformations give us an increase of 2.73 BLEU points , Verbs improve the result by only 0.8 points and improvement with Adverbs is even lower.
Related Work
(2007) have integrated more syntax in a factored translation approach by using CCG su-pertags as a separate factor and have reported a 0.46 BLEU point improvement in Dutch-to-English translations.
Related Work
In the context of reordering, one recent work (Xu et al., 2009), was able to get an improvement of 0.6 BLEU points by using source syntactic analysis and a constituent reordering scheme like ours for English-to-Turkish translation, but without using any morphology.
BLEU points is mentioned in 3 sentences in this paper.
Topics mentioned in this paper: