Name
Abstract | ||
|---|---|---|
When hierarchical phrase-based statistical machine translation systems are used for language translation, sometimes the translations' content words were lost: source-side content words is empty when translated into target texts during decoding. Although the translations' BLEU score is very high, it is difficult to understand the translations because of the loss of the content words. In this paper, we propose a basic and efficient method for phrase filtering, with which the phrase' content words translation are checked to decide whether to use the phrase in decoding or not. The experimental results show that the proposed method alleviates the problem of the loss content words' and improves the BLEU scores. © 2013 Springer-Verlag. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-45185-0_51 | CLSW |
Keywords | Field | DocType |
content words,hierarchical phrase-based model,phrase filtering | Language translation,Computer science,Machine translation,Filter (signal processing),Phrase,Speech recognition,Artificial intelligence,Natural language processing,Decoding methods | Conference |
Volume | Issue | ISSN |
8229 LNAI | null | 16113349 |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xing Wang | 1 | 13 | 10.58 |
| Jun Xie | 2 | 8 | 6.15 |
| Linfeng Song | 3 | 87 | 16.75 |
| Yajuan Lü | 4 | 276 | 20.00 |
| Jianmin Yao | 5 | 131 | 16.96 |