We make a detailed analysis on the Chinese-English translation results that are affected by our paraphrase rules.

The analysis is carried out on the IWSLT 2007 Chinese-English test set, 84 out of 489 input sentences have been affected by paraphrases, and the statistic of human evaluation is shown in Table 8.

The experiments were conducted in both Chinese-English and English-Chinese directions for the oral group, and Chinese-English direction for the news group.

corpora, including the Chinese-English Sentence Aligned Bilingual Corpus (CLDC-LAC-2003-004) and the Chinese-English Parallel Corpora (CLDC-LAC-2003-006).

For testing and developing, we used six Chinese-English development corpora of IWSLT 2008.

For our experiments, we tuned a on Chinese-English data, setting it to 0.25 and keeping this value for the other language pairs.

The large data condition uses training data from NIST3 2009 ( Chinese-English track).

We are currently investigating why PORT tuning gives higher BLEU scores than BLEU tuning for Chinese-English and German-English.

PORT outperforms Qmean on seven of the eight automatic scores shown for small and large Chinese-English .

To demonstrate the effect of the {O-norm on the IBM models, we performed experiments on four translation tasks: Arabic-English, Chinese-English , and Urdu-English from the NIST Open MT Evaluation, and the Czech-English translation from the Workshop on Machine Translation (WMT) shared task.

0 Chinese-English : selected data from the constrained task of the NIST 2009 Open MT Evaluation.3

For Arabic-English and Chinese-English , we used 346 and 184 hand-aligned sentences from LDC2006E86 and LDC2006E93.

Experimental results on Chinese-English translation across four test sets demonstrate significant improvements of the HD-HPB model over both Chiang’s HPB and a source-side SAMT—style refined version of HPB.

Figure 1: An example word alignment for a Chinese-English sentence pair with the dependency parse tree for the Chinese sentence.

Experiments on Chinese-English translation using four NIST MT test sets show that our HD-HPB model significantly outperforms Chiang’s HPB as well as a SAMT—style refined version of HPB.