Abstract
We present an Open Source framework called MOOD developed in order tofacilitate the development of a Statistical Machine Translation Decoder.MOOD has been modularized using an object-oriented approach which makes itespecially suitable for the fast development of state-of-the-art decoders. Asa proof of concept, a clone of the pharaoh decoder has been implemented andevaluated. This clone named ramses is part of the current distribution of MOOD.- Anthology ID:
- L06-1328
- 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/542_pdf.pdf
- DOI:
- Cite (ACL):
- Alexandre Patry, Fabrizio Gotti, and Philippe Langlais. 2006. MOOD: A Modular Object-Oriented Decoder for Statistical Machine Translation. In Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06), Genoa, Italy. European Language Resources Association (ELRA).
- Cite (Informal):
- MOOD: A Modular Object-Oriented Decoder for Statistical Machine Translation (Patry et al., LREC 2006)
- PDF:
- http://www.lrec-conf.org/proceedings/lrec2006/pdf/542_pdf.pdf