Hybrid Machine Translation Applied to Media Monitoring

Hassan Sawaf, Braddock Gaskill, Michael Veronis


Abstract
In this paper, a system is presented that recognizes spoken utterances in Arabic Dialects which are translated into text in English. The input is recorded from a broadcast channel and recognized using automatic speech recognition that recognize Modern Standard Arabic and Iraqi Colloquial Arabic. The recognized utterances are normalized into Modern Standard Arabic and the output of this Modern Standard Arabic interlingua is then translated by a hybrid machine translation system, combining statistical and rule-based features.
Anthology ID:
2008.amta-govandcom.21
Volume:
Proceedings of the 8th Conference of the Association for Machine Translation in the Americas: Government and Commercial Uses of MT
Month:
October 21-25
Year:
2008
Address:
Waikiki, USA
Venue:
AMTA
SIG:
Publisher:
Association for Machine Translation in the Americas
Note:
Pages:
440–447
Language:
URL:
https://aclanthology.org/2008.amta-govandcom.21
DOI:
Bibkey:
Cite (ACL):
Hassan Sawaf, Braddock Gaskill, and Michael Veronis. 2008. Hybrid Machine Translation Applied to Media Monitoring. In Proceedings of the 8th Conference of the Association for Machine Translation in the Americas: Government and Commercial Uses of MT, pages 440–447, Waikiki, USA. Association for Machine Translation in the Americas.
Cite (Informal):
Hybrid Machine Translation Applied to Media Monitoring (Sawaf et al., AMTA 2008)
Copy Citation:
PDF:
https://aclanthology.org/2008.amta-govandcom.21.pdf