- -

Log-Linear Weight Optimization Using Discriminative Ridge Regression Method in Statistical Machine Translation

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

Log-Linear Weight Optimization Using Discriminative Ridge Regression Method in Statistical Machine Translation

Show full item record

Chinea-Ríos, M.; Sanchis Trilles, G.; Casacuberta Nolla, F. (2017). Log-Linear Weight Optimization Using Discriminative Ridge Regression Method in Statistical Machine Translation. Lecture Notes in Computer Science. 10255:32-41. doi:10.1007/978-3-319-58838-4_4

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/103609

Files in this item

Item Metadata

Title: Log-Linear Weight Optimization Using Discriminative Ridge Regression Method in Statistical Machine Translation
Author: Chinea-Ríos, Mara Sanchis Trilles, Germán Casacuberta Nolla, Francisco
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Issued date:
Abstract:
[EN] We present a simple and reliable method for estimating the log-linear weights of a state-of-the-art machine translation system, which takes advantage of the method known as discriminative ridge regression (DRR). Since ...[+]
Subjects: Statistical machine translation , Log-linear model , Discriminative ridge regression
Copyrigths: Reserva de todos los derechos
Source:
Lecture Notes in Computer Science. (issn: 0302-9743 )
DOI: 10.1007/978-3-319-58838-4_4
Publisher:
Springer-Verlag
Publisher version: https://doi.org/10.1007/978-3-319-58838-4_4
Conference name: 8th Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2017)
Conference place: Faro, Portugal
Conference date: June 20-23,2017
Project ID:
GV/PROMETEOII/2014/030
Thanks:
The research leading to these results has received funding fromthe Generalitat Valenciana under grant PROMETEOII/2014/030 and the FPI (2014) grant by Universitat Politècnica de València.
Type: Artículo Comunicación en congreso

References

Och, F.J.: Minimum error rate training in statistical machine translation. In: Proceedings of ACL, pp. 160–167 (2003)

Crammer, K., Dekel, O., Keshet, J., Shalev-Shwartz, S., Singer, Y.: Online passive-aggressive algorithms. J. Mach. Learn. Res. 7, 551–585 (2006)

Och, F.J., Ney, H.: A systematic comparison of various statistical alignment models. Comput. Linguist. 29, 19–51 (2003) [+]
Och, F.J.: Minimum error rate training in statistical machine translation. In: Proceedings of ACL, pp. 160–167 (2003)

Crammer, K., Dekel, O., Keshet, J., Shalev-Shwartz, S., Singer, Y.: Online passive-aggressive algorithms. J. Mach. Learn. Res. 7, 551–585 (2006)

Och, F.J., Ney, H.: A systematic comparison of various statistical alignment models. Comput. Linguist. 29, 19–51 (2003)

Koehn, P.: Statistical Machine Translation. Cambridge University Press, Cambridge (2010)

Martínez-Gómez, P., Sanchis-Trilles, G., Casacuberta, F.: Online adaptation strategies for statistical machine translation in post-editing scenarios. Pattern Recogn. 45(9), 3193–3203 (2012)

Cherry, C., Foster, G.: Batch tuning strategies for statistical machine translation. In: Proceedings of NAACL, pp. 427–436 (2012)

Sanchis-Trilles, G., Casacuberta, F.: Log-linear weight optimisation via Bayesian adaptation in statistical machine translation. In: Proceedings of ACL, pp. 1077–1085 (2010)

Marie, B., Max, A.: Multi-pass decoding with complex feature guidance for statistical machine translation. In: Proceedings of ACL, pp. 554–559 (2015)

Hopkins, M., May, J.: Tuning as ranking. In: Proceedings of EMNLP, pp. 1352–1362 (2011)

Stauffer, C., Grimson, W.E.L.: Learning patterns of activity using real-time tracking. Pattern Anal. Mach. Intell. 22(8), 747–757 (2000)

Koehn, P., Hoang, H., Birch, A., Callison-Burch, C., Federico, M., Bertoldi, N., Cowan, B., Shen, W., Moran, C., Zens, R., Dyer, C., Bojar, O., Constantin, A., Herbst, E.: Moses: open source toolkit for statistical machine translation. In: Proceedings of ACL, pp. 177–180 (2007)

Kneser, R., Ney, H.: Improved backing-off for m-gram language modeling. In: Proceedings of ICASSP, pp. 181–184 (1995)

Stolcke, A.: Srilm-an extensible language modeling toolkit. In: Proceedings of ICSLP, pp. 901–904 (2002)

Papineni, K., Roukos, S., Ward, T., Zhu, W.-J.: BLEU: a method for automatic evaluation of machine translation. In: Proceedings of ACL, pp. 311–318 (2002)

Chen, B., Cherry, C.: A systematic comparison of smoothing techniques for sentence-level BLEU. In: Proceedings of WMT, pp. 362–367 (2014)

Snover, M., Dorr, B.J., Schwartz, R., Micciulla, L., Makhoul, J.: A study of translation edit rate with targeted human annotation. In: Proceedings of AMTA, pp. 223–231 (2006)

Tiedemann, J.: News from opus-a collection of multilingual parallel corpora with tools and interfaces. In: Proceedings of RANLP, pp. 237–248 (2009)

Tiedemann, J.: Parallel data, tools and interfaces in opus. In: Proceedings of LREC, pp. 2214–2218 (2012)

[-]

This item appears in the following Collection(s)

Show full item record