Abstract
In this paper we report an experiment of an automated metric used to analyse the grammaticality of machine translation output. The approach (Rajman, Hartley, 2001) is based on the distribution of the linguistic information within a translated text, which is supposed similar between a learning corpus and the translation. This method is quite inexpensive, since it does not need any reference translation. First we describe the experimental method and the different tests we used. Then we show the promising results we obtained on the CESTA data, and how they correlate well with human judgments.- Anthology ID:
- L06-1455
- Volume:
- Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
- Month:
- May
- Year:
- 2006
- Address:
- Genoa, Italy
- Editors:
- Nicoletta Calzolari, Khalid Choukri, Aldo Gangemi, Bente Maegaard, Joseph Mariani, Jan Odijk, Daniel Tapias
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- Language:
- URL:
- http://www.lrec-conf.org/proceedings/lrec2006/pdf/729_pdf.pdf
- DOI:
- Cite (ACL):
- O. Hamon and M. Rajman. 2006. X-Score: Automatic Evaluation of Machine Translation Grammaticality. In Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06), Genoa, Italy. European Language Resources Association (ELRA).
- Cite (Informal):
- X-Score: Automatic Evaluation of Machine Translation Grammaticality (Hamon & Rajman, LREC 2006)
- PDF:
- http://www.lrec-conf.org/proceedings/lrec2006/pdf/729_pdf.pdf