The EUTRANS-I corpus
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资源简介:
EUTRANS-I is a simple translation corpus which was produced and used in the EuTrans project. It corresponds to the so called "Traveller Task" which involves human-to-human communication situations in the front-desk of a hotel. Bilingual data were produced semi-automatically in three language pairs on the base of small "seed corpora", obtained from several traveler-oriented booklets.
In using this corpus you agree that:
1. This corpus may be used free of cost for non commercial purposes.
2. If commercial use is intended, please first contact:
Dr. Enrique Vidal
Pattern Recognition and Language Technologies Research Center
Cno. de Vera s/n
E - 46071 Valencia
tel: +34 / 96 387 93 51
fax: +34 / 96 387 73 58
e-mail: evidal@prhlt.upv.es
3. In case of redistribution, this file must be distributed as is
along with the corpus.
4. Any publication derived from the use of this corpus must reference
the EuTrans project ("Example-based langUage TRANslation Systems",
EU Esprit #30268) and appropriate scholarly citation(s), such as:
J.C. Amengual, J.M. Benedí, F. Casacuberta, A. Castaño,
A. Castellanos, V. Jiménez, D. Llorens, A. Marzal, F. Prat,
E. Vidal, and J.M. Vilar: "Using categories in the EuTrans
system". In ACL-ELSNET Workshoop on Spoken Language Translation,
pages 44-53, Madrid (Spain), July 1997.
J.C.Amengual, J.M.Benedí F.Casacuberta, A.Castaño, A.Castellanos,
V.Jiménez, D.Llorens, A.Marzal, M.Pastor, F.Prat, E.Vidal,
J.M.Vilar: "The EuTrans-I Speech Translation System". Machine
Translation. Vol.15, pp.75-103, 2001.
F.Casacuberta, H.Ney, F.J.Och, J.M.Vilar, E.Vidal, S.Barrachina,
I.García-Varea, C.Martínez D.Llorens, S.Molau, F.Nevado, M.Pastor,
D.Picó, A.Sanchís: "Some ap- proaches to statistical and
finite-state speech-to-speech translation". Computer Speech and
Language, Vol.18, pp.25-47, 2004.
F.Casacuberta, E.Vidal, D.Picó: "Inference of finite-state
transducers from regular languages". Pattern Recognition. Vol.38,
pp.1431-1443, 2005.
F.Casacuberta, E.Vidal: "Learning finite-state models for machine
translation". Machine Learning, Vol.66(1), pp.69-91, 2007.
创建时间:
2021-10-20



