TY - GEN
T1 - Generating complex morphology for machine translation
AU - Minkov, Einat
AU - Toutanova, Kristina
AU - Suzuki, Hisami
PY - 2007
Y1 - 2007
N2 - We present a novel method for predicting inflected word forms for generating morphologically rich languages in machine translation. We utilize a rich set of syntactic and morphological knowledge sources from both source and target sentences in a probabilistic model, and evaluate their contribution in generating Russian and Arabic sentences. Our results show that the proposed model substantially outperforms the commonly used baseline of a trigram target language model; in particular, the use of morphological and syntactic features leads to large gains in prediction accuracy. We also show that the proposed method is effective with a relatively small amount of data.
AB - We present a novel method for predicting inflected word forms for generating morphologically rich languages in machine translation. We utilize a rich set of syntactic and morphological knowledge sources from both source and target sentences in a probabilistic model, and evaluate their contribution in generating Russian and Arabic sentences. Our results show that the proposed model substantially outperforms the commonly used baseline of a trigram target language model; in particular, the use of morphological and syntactic features leads to large gains in prediction accuracy. We also show that the proposed method is effective with a relatively small amount of data.
UR - http://www.scopus.com/inward/record.url?scp=84860527733&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84860527733
SN - 9781932432862
T3 - ACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics
SP - 128
EP - 135
BT - ACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics
T2 - 45th Annual Meeting of the Association for Computational Linguistics, ACL 2007
Y2 - 23 June 2007 through 30 June 2007
ER -