Name
Abstract | ||
|---|---|---|
The purpose of this paper is to provide guidelines for building a word alignment evaluation scheme. The notion of word alignment quality depends on the application: here we review standard scoring metrics for full text alignment and give explanations on how to use them better. We discuss strategies to build a reference corpus, and show that the ratio between ambiguous and unambiguous links in the reference has a great impact on scores measured with these metrics. In particular, automatically computed alignments with higher precision or higher recall can be favoured depending on the value of this ratio. Finally, we suggest a strategy to build a reference corpus particularly adapted to applications where recall plays a significant role, like in machine translation. The manually aligned corpus we built for the Spanish-English European Parliament corpus is also described. This corpus is freely available. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/s10579-005-4822-5 | Language Resources and Evaluation |
Keywords | Field | DocType |
alignment error rate,bilingual,evaluation,gold standard,manual alignment,parallel corpus,precision,recall,word alignment | Computer science,Computational linguistics,Machine translation,Speech recognition,Natural language processing,Artificial intelligence,Text alignment,Recall | Journal |
Volume | Issue | ISSN |
39 | 4 | 1572-0218 |
Citations | PageRank | References |
22 | 1.06 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Patrik Lambert | 1 | 277 | 23.36 |
| Adrià de Gispert | 2 | 472 | 35.22 |
| Rafael E. Banchs | 3 | 566 | 63.64 |
| José B. Mariño | 4 | 510 | 64.66 |