A study of english vietnamese statistical machine translation = nghiên cứu về dịch máy thống kê anh việt

A Study of English-Vietnamese Statistical Machine Translation Hoang Cuong Faculty of Information Technology University of Engineering and Technology Vietnam National University, Hanoi Supervised by Prof Pham Bao Son A thesis submitted in fulfillment of the requirements for the degree of Master of Computer Science December, 2012 ORIGINALITY STATEMENT ‘I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, or substantial proportions of material which have been accepted for the award of any other degree or diploma at Vietnam National University, Hanoi or any other educational institution, except where due acknowledgement is made in the thesis Any contribution made to the research by others, with whom I have worked at Institute for INFOCOMM Research, Singapore (I2R), Vietnam Institute for Advanced Study in Mathematics, Hanoi (VIASM) or elsewhere, is explicitly acknowledged in the thesis I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project’s design and conception or in style, presentation and linguistic expression is acknowledged.’ Signed i APPROVAL I, the supervisor, hereby approve that the Thesis in its current form is ready as the final version at the University of Engineering and Technology, Vietnam National University, Hanoi Prof Pham Bao Son ii iii x ABSTRACT Previous works from Vietnamese statistical machine translation (SMT) community research just focus on some top “researches” of the field Some are based on the ideas which are really simple We lack a fundamental work on the core of SMT system to make a significantly solid work on the statistical English-Vietnamese translation We also lack some large bilingual corpora with high quality This work will overcome that problem We present a fundamental and primitive study of English-Vietnamese statistical machine translation We make a serious research to the core of any SMT system such as exploiting bilingual corpora, improving word alignment or phrase translation modeling quality We also focus on developing a better evaluation metric for tuning SMT system We especial try our best to make a fundamental and solid work on building or improving the performance of the English-Vietnamese SMT system in overall Though we focus on the English-Vietnamese pair In every aspect, we also deploy and compare our research to the pair English-French to have a deeper view We hope our work research will be a solid work for other studies on deploying and improving the SMT for English-Vietnamese machine translation systems Publications: • Cuong Hoang, Cuong-Anh, Le, Thai-Phuong, Nguyen, Bao-Tu, Ho Exploiting Non-Parallel Corpora for Statistical Machine Translation In Proceedings of the international conference on Information and Communication Technologies (RIVF 2012)1 • Cuong Hoang, Cuong-Anh, Le, Son-Bao, Pham A Systematic Comparison Between Various Statistical Alignment Models for Statistical English-Vietnamese Phrase-Based Translation In Proceedings of the 4th international conference on Knowledge and Systems Engineering (KSE 2012) Best Student Paper Award iv v • Cuong Hoang, Cuong-Anh, Le, Son-Bao, Pham Refining Lexical Translation Training Scheme for Improving The Quality of Statistical Phrase-Based Translation In Proceedings of the 3th international symposium on Information and Communication Technology (SoICT 2012) • Cuong Hoang, Cuong-Anh, Le, Son-Bao, Pham Improving the Quality of Word Alignment By Integrating Pearson’s Chi-square Test Information In Proceedings of the international conference on Asian Language Processing (IALP 2012) ACKNOWLEDGEMENTS Life is so valuable when we found something which is merit to chase First, I would like to express my deep gratitude to my supervisor - Prof Pham Bao Son - who has been also my iconic researcher in Vietnam since I was as a freshman I also want to thank Prof Le Anh Cuong for his so-much-careful supervision for me, though he not register me as his student to the school For both of them, I own their patient guidance and support through-out the years I would like to give my honest appreciation to my other unofficial supervisors - Prof Ho Tu Bao (JAIST, Japan), Prof Zhang Min (I2R, Singapore), Prof Nguyen Xuan Long (Michigan, USA) - for their great support They are, in diversified perspectives, have been helping my passion in Computer Science increases intensively I sincerely acknowledge Vietnam National University, Hanoi I want to thank some of my best teachers - Dr Nguyen Van Vinh, Dr Nguyen Phuong Thai or Prof Nguyen Le Minh (JAIST, Japan) who make many useful discussion Especially, I want to give my honest appreciation to the Statistical Language Processing Laboratory I work at Infocomm for Institute Research, Singapore (I2R) for the infrastructure and other uncountable support I would like to thank my Chinese friends here - Yun Huang, Prof Yue Zhang, Jun SUN and Yanxia Qin I wish I could work with them as much longer as possible I also want to make a appreciation to some of my best friends - Dinh Xuan Nhat, Nguyen Dao Thai - for their helps in my work Finally, this thesis would not have been possible without the support and love of my Family - Dad, Mum, my Sister - Lan Ni and her small family Without their support in variety perspectives, I sure that I cannot finish my Master Degree in this way! And To love, My Mimosa ♥ !!! vi Table of Contents Introduction 1.1 Statistical Machine Translation - An Overview 1.2 Literature Survey on English-Vietnamese Machine Translation 1.3 Our Work 1.4 Thesis Contents 1.4.1 Exploiting non-parallel corpora for statistical machine translation 1.4.2 Systematic comparison between various statistical alignment models for statistical English-Vietnamese phrase-based translation 1.4.3 Improving word alignment models 1.4.4 Improving phrase translation modeling 1.4.5 Developing an evaluation metric for SMT vii 2 9 10 10 11 11 12 List of Figures 1.1 1.2 1.3 1.4 The architecture of the translation approach based on source-channel models An example of word alignments between the pair of English-French An example of phrase alignments between the pair of English-German The architecture of the translation approach based on log-linear models viii 4 12 Chapter Introduction directly integrates word-to-word translation parameter into phrase translation weight estimation This method reduces deeply the effect of noise reduction phenomenon We evaluate our approach on the WMT10 French-to-English task, and show significant improvements on parallel data sets of different scales By gaining these advantages, we also show the much better improvement for the upgraded systems trained on the tasks when improved word alignment quality 1.4.5 Developing an evaluation metric for SMT Tuning the parameters from a log-linear model is an important step to find out the best fitting weights for model Modern tuning techniques directly use automatic evaluation metrics as the training criteria for optimizing the system This aspect is very important since we have been forced to find good evaluation metrics Many machine translation evaluation metrics have been proposed after the seminal BLEU metric They have been found to outperform BLEU, demonstrated by the better correlations with human judgments We hope that to train machine translation systems using these new metrics can lead directly to advances in automatic machine translation However, to our knowledge though, there has been no unambiguous report that we can improve a state-of-the-art machine translation system over its BLEU-tuned baseline In this work, we will present a novel automatic evaluation metric, entitled SEMI It bases on the phrasal overlapping measurement scheme and especially favours the grading scheme with longer n-gram matchings We evaluate our metric on the the WMT10 French-to-English task We will show that the evaluation metric is the first one significantly led directly to advances in automatic machine translation on parallel data sets of different scales Bibliography AbduI-Rauf, S., & Schwenk, H (2009) On the use of comparable corpora to improve smt performance Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (pp 16–23) Stroudsburg, PA, USA: Association for Computational Linguistics Abdul-Rauf, S., & Schwenk, H (2009) Exploiting comparable corpora with ter and terp Proceedings of the 2nd Workshop on Building and Using Comparable Corpora: from Parallel to Non-parallel Corpora (pp 46–54) Stroudsburg, PA, USA: Association for Computational Linguistics Abdul Rauf, S., & Schwenk, H (2011) Parallel sentence generation from comparable corpora for improved smt Machine Translation, 25, 341–375 Achananuparp, P., Hu, X., & Shen, X (2008) The evaluation of sentence similarity measures Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery (pp 305–316) Berlin, Heidelberg: Springer-Verlag Adafre, S F., & de Rijke, M (2006) Finding Similar Sentences across Multiple Languages in Wikipedia Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics, 62–69 Banerjee, S., & Lavie, A (2005) Meteor: An automatic metric for mt evaluation with improved correlation with human judgments (pp 65–72 ) Banerjee, S., & Pedersen, T (2003) Extended gloss overlaps as a measure of semantic relatedness Proceedings of the 18th international joint conference on Artificial intelligence (pp 805–810) San Francisco, CA, USA: Morgan Kaufmann Publishers Inc Bertoldi, N., Haddow, B., & Fouet, J.-B (2009) Improved Minimum Error Rate Training in Moses The Prague Bulletin of Mathematical Linguistics, 91, 7–16 13 14 Bibliography Birch, A., & Osborne, M (2011) Reordering metrics for mt Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - 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Exploiting non-parallel corpora for statistical machine translation 1.4.2 Systematic comparison between various statistical alignment models for statistical English- Vietnamese phrase-based translation