Silvestre-Cerdà, Joan Albert; Andrés-Ferrer, Jesús; Civera, Jorge Explicit length modelling for statistical machine translation Journal Article Pattern Recognition, 45 (9), pp. 3183 - 3192, 2012, ISSN: 0031-3203. Abstract | Links | BibTeX | Tags: Length modelling, Log-linear models, Phrase-based models, Statistical machine translation @article{Silvestre-Cerdà2012a,
title = {Explicit length modelling for statistical machine translation},
author = {Joan Albert Silvestre-Cerdà and Jesús Andrés-Ferrer and Jorge Civera},
url = {http://hdl.handle.net/10251/34996},
issn = {0031-3203},
year = {2012},
date = {2012-01-01},
journal = {Pattern Recognition},
volume = {45},
number = {9},
pages = {3183 - 3192},
abstract = {Explicit length modelling has been previously explored in statistical pattern recognition with successful results. In this paper, two length models along with two parameter estimation methods and two alternative parametrisation for statistical machine translation (SMT) are presented. More precisely, we incorporate explicit bilingual length modelling in a state-of-the-art log-linear SMT system as an additional feature function in order to prove the contribution of length information. Finally, a systematic evaluation on reference SMT tasks considering different language pairs prove the benefits of explicit length modelling.},
keywords = {Length modelling, Log-linear models, Phrase-based models, Statistical machine translation},
pubstate = {published},
tppubtype = {article}
}
Explicit length modelling has been previously explored in statistical pattern recognition with successful results. In this paper, two length models along with two parameter estimation methods and two alternative parametrisation for statistical machine translation (SMT) are presented. More precisely, we incorporate explicit bilingual length modelling in a state-of-the-art log-linear SMT system as an additional feature function in order to prove the contribution of length information. Finally, a systematic evaluation on reference SMT tasks considering different language pairs prove the benefits of explicit length modelling. |
Silvestre-Cerdà, Joan Albert; Andrés-Ferrer, Jesús ; Civera, Jorge Explicit Length Modelling for Statistical Machine Translation Incollection Vitrià, Jordi ; Sanches, JoãoMiguel ; Hernández, Mario (Ed.): Pattern Recognition and Image Analysis (IbPRIA 2011), 6669 , pp. 273-280, Springer Berlin Heidelberg, 2011, ISBN: 978-3-642-21256-7. Abstract | Links | BibTeX | Tags: Length modelling, Log-linear models, Phrase-based models, Statistical machine translation @incollection{Silvestre-Cerdà2011,
title = {Explicit Length Modelling for Statistical Machine Translation},
author = { Joan Albert Silvestre-Cerdà and Jesús Andrés-Ferrer and Jorge Civera},
editor = {Vitrià, Jordi and Sanches, JoãoMiguel and Hernández, Mario},
url = {http://hdl.handle.net/10251/35749
http://dx.doi.org/10.1007/978-3-642-21257-4_34},
isbn = {978-3-642-21256-7},
year = {2011},
date = {2011-01-01},
booktitle = {Pattern Recognition and Image Analysis (IbPRIA 2011)},
volume = {6669},
pages = {273-280},
publisher = {Springer Berlin Heidelberg},
series = {Lecture Notes in Computer Science},
abstract = {Explicit length modelling has been previously explored in statistical pattern recognition with successful results. In this paper, two length models along with two parameter estimation methods for statistical machine translation (SMT) are presented. More precisely, we incorporate explicit length modelling in a state-of-the-art log-linear SMT system as an additional feature function in order to prove the contribution of length information. Finally, promising experimental results are reported on a reference SMT task.},
keywords = {Length modelling, Log-linear models, Phrase-based models, Statistical machine translation},
pubstate = {published},
tppubtype = {incollection}
}
Explicit length modelling has been previously explored in statistical pattern recognition with successful results. In this paper, two length models along with two parameter estimation methods for statistical machine translation (SMT) are presented. More precisely, we incorporate explicit length modelling in a state-of-the-art log-linear SMT system as an additional feature function in order to prove the contribution of length information. Finally, promising experimental results are reported on a reference SMT task. |