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Discriminative ridge regression algorithm for adaptation in statistical machine translation

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Discriminative ridge regression algorithm for adaptation in statistical machine translation

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Chinea-Ríos, M.; Sanchis-Trilles, G.; Casacuberta Nolla, F. (2019). Discriminative ridge regression algorithm for adaptation in statistical machine translation. Pattern Analysis and Applications. 22(4):1293-1305. https://doi.org/10.1007/s10044-018-0720-5

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/157503

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Title: Discriminative ridge regression algorithm for adaptation 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 algorithm , Log-linear weights , Adaptation
Copyrigths: Reserva de todos los derechos
Source:
Pattern Analysis and Applications. (issn: 1433-7541 )
DOI: 10.1007/s10044-018-0720-5
Publisher:
Springer-Verlag
Publisher version: https://doi.org/10.1007/s10044-018-0720-5
Project ID:
GV/PROMETEO/2018/004
MINISTERIO DE ECONOMIA Y EMPRESA/TIN2015-70924-C2-1-R
GENERALITAT VALENCIANA/PROMETEO/2019/121
Thanks:
The research leading to these results were partially supported by projects CoMUN-HaT-TIN2015-70924-C2-1-R (MINECO/FEDER) and PROMETEO/2018/004. We also acknowledge NVIDIA for the donation of a GPU used in this work.
Type: Artículo

References

Barrachina S, Bender O, Casacuberta F, Civera J, Cubel E, Khadivi S, Lagarda A, Ney H, Tomás J, Vidal E et al (2009) Statistical approaches to computer-assisted translation. Comput Ling 35(1):3–28

Bojar O, Buck C, Federmann C, Haddow B, Koehn P, Monz C, Post M, Specia L (eds) (2014) Proceedings of the ninth workshop on statistical machine translation. Association for Computational Linguistics

Brown PF, Pietra VJD, Pietra SAD, Mercer RL (1993) The mathematics of statistical machine translation: parameter estimation. Comput Ling 19:263–311 [+]
Barrachina S, Bender O, Casacuberta F, Civera J, Cubel E, Khadivi S, Lagarda A, Ney H, Tomás J, Vidal E et al (2009) Statistical approaches to computer-assisted translation. Comput Ling 35(1):3–28

Bojar O, Buck C, Federmann C, Haddow B, Koehn P, Monz C, Post M, Specia L (eds) (2014) Proceedings of the ninth workshop on statistical machine translation. Association for Computational Linguistics

Brown PF, Pietra VJD, Pietra SAD, Mercer RL (1993) The mathematics of statistical machine translation: parameter estimation. Comput Ling 19:263–311

Callison-Burch C, Koehn P, Monz C, Peterson K, Przybocki M, Zaidan OF (2010) Findings of the 2010 joint workshop on statistical machine translation and metrics for machine translation. In: Proceedings of the annual meeting of the association for computational linguistics, pp 17–53

Chen B, Cherry C (2014) A systematic comparison of smoothing techniques for sentence-level bleu. In: Proceedings of the workshop on statistical machine translation, pp 362–367

Cherry C, Foster G (2012) Batch tuning strategies for statistical machine translation. In: Proceedings of the North American chapter of the association for computational linguistics, pp 427–436

Clark JH, Dyer C, Lavie A, Smith NA (2011) Better hypothesis testing for statistical machine translation: controlling for optimizer instability. In: Proceedings of the annual meeting of the association for computational linguistics, pp 176–181

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

Hasler E, Haddow B, Koehn P (2011) Margin infused relaxed algorithm for moses. Prague Bull Math Ling 96:69–78

Hopkins M, May J (2011) Tuning as ranking. In: Proceedings of the conference on empirical methods in natural language processing, pp 1352–1362

Kneser R, Ney H (1995) Improved backing-off for m-gram language modeling. In: Proceedings of the international conference on acoustics, speech and signal processing, pp 181–184

Koehn P (2005) Europarl: a parallel corpus for statistical machine translation. In: Proceedings of the machine translation summit, pp 79–86

Koehn P (2010) Statistical machine translation. Cambridge University Press, Cambridge

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 (2007) Moses: open source toolkit for statistical machine translation. In: Proceedings of the annual meeting of the association for computational linguistics, pp 177–180

Lavie MDA (2014) Meteor universal: language specific translation evaluation for any target language. In: Proceedings of the annual meeting of the association for computational linguistics, pp 376–387

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

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

Nakov P, Vogel S (2017) Robust tuning datasets for statistical machine translation. arXiv:1710.00346

Neubig G, Watanabe T (2016) Optimization for statistical machine translation: a survey. Comput Ling 42(1):1–54

Och FJ (2003) Minimum error rate training in statistical machine translation. In: Proceedings of the annual meeting of the association for computational linguistics, pp 160–167

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

Papineni K, Roukos S, Ward T, Zhu WJ (2002) Bleu: a method for automatic evaluation of machine translation. In: Proceedings of the international conference on acoustics, speech and signal processing, pp 311–318

Sanchis-Trilles G, Casacuberta F (2010) Log-linear weight optimisation via Bayesian adaptation in statistical machine translation. In: Proceedings of the annual meeting of the association for computational linguistics, pp 1077–1085

Sanchis-Trilles G, Casacuberta F (2015) Improving translation quality stability using Bayesian predictive adaptation. Comput Speech Lang 34(1):1–17

Snover M, Dorr B, Schwartz R, Micciulla L, Makhoul J (2006) A study of translation edit rate with targeted human annotation. In: Proceedings of the annual meeting of the association for machine translation in the Americas, pp 223–231

Sokolov A, Yvon F (2011) Minimum error rate training semiring. In: Proceedings of the annual conference of the European association for machine translation, pp 241–248

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

Stolcke A (2002) Srilm—an extensible language modeling toolkit. In: Proceedings of the international conference on spoken language processing, pp 901–904

Tiedemann J (2009) News from opus—a collection of multilingual parallel corpora with tools and interfaces. In: Proceedings of the recent advances in natural language processing, pp 237–248

Tiedemann J (2012) Parallel data, tools and interfaces in opus. In: Proceedings of the language resources and evaluation conference, pp 2214–2218

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