Search Research Papers Google Translate


FILE – In this Tuesday, March 23, 2010 file photo, the Google logo is seen at the Google headquarters in Brussels. The European Union’s competition chief Margrethe Vestager is expected on Wednesday, April 15, 2015 to file a complaint alleging Google has been abusing its dominance in Internet searches. (AP Photo/Virginia Mayo, File)

Any students using Google Translate to cheat on their Spanish homework can rejoice. The foreign-language translation tool is about to get a whole lot more accurate.

Last week,  Google launched an updated translation tool that utilizes sophisticated artificial intelligence to produce startlingly accurate language translations. While the tool has been used to successfully translate between English and Spanish, French and Chinese in a research setting, it’s only available currently to everyday users for Chinese to English translations. The new system, which uses deep machine learning to mimic the functioning of a human brain, is called the Google Neural Machine Translation system, or GNMT.

To test the system, Google had human raters evaluate translations on a scale from 0 to 6. Translating from English to Spanish, the new Google tool’s translation was rated an average of 5.43; human translators earned an average of 5.5. For Chinese to English, the only public-facing option that currently utilizes the new system, Google Translate was rated an average of 4.3 while human translators got 4.6.

Overall, across all three languages, Google said its new tool  is 60 percent more accurate than the old Google Translate tool, which used phrase-based machine translation, or PBMT. “With the previous PBMT model, when we translate a sentence from one language to another, we would translate one word or a phrase in the source sentence at a time, then re-order the words in the correct grammar of the target language,” said Quoc Le, a Google researcher who worked on the project. “The complication is language has a lot of ambiguity. In our new GNMT system, we treat a whole sentence as a unit, and translate [the words] in a group.”

The complexity of a translation machine that can digest entire phrases rather than rely on word-by-word translation are somewhat lost even on the researchers themselves. In an interview with MIT Technology review, Le called the new translator “unsettling. But we’ve tested it in a lot of places and it just works.”

Despite its improved accuracy,  the GNMT model still mistranslates rare terms and occasionally drops words. And it hasn’t acquired any common sense. Given the sentence “The trophy cannot fit in the cabinet because it’s too big,” the model could mistranslate because it doesn’t know which “it” is the one that’s too big. “GNMT doesn’t have a model of how the world actually works yet,” said Le.

While the tool is only being offered for one language pair now, Google said it plans to roll out the new system to more of the 10,000 language pairs that Google Translate currently supports. “We hope this research increases the ability for people around the world to communicate with others regardless of what languages they speak,” said Le.

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    Learning how to explain neural networks: PatternNet and PatternAttribution

    Pieter-jan Kindermans, Kristof T. Schütt, Maximilian Alber, Klaus-Robet Müller, Dumitru Erhan, Been Kim, Sven Dähne

    ICLR (2018) (to appear)

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    A Polynomial-Time Dynamic Programming Algorithm for Phrase-Based Decoding with a Fixed Distortion Limit

    Yin-Wen Chang, Michael Collins

    Transactions of the Association for Computational Linguistics (TACL), vol. 5 (2017), pp. 59-71

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    Efficient Attention using a Fixed-Size Memory Representation

    Denny Britz, Melody Guan, Thang Luong

    EMNLP (2017)

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    Massive Exploration of Neural Machine Translation Architectures

    Denny Britz, Anna Goldie, Thang Luong, Quoc Le

    EMNLP (2017)

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    Source-Side Left-to-Right or Target-Side Left-to-Right? An Empirical Comparison of Two Phrase-Based Decoding Algorithms

    Yin-Wen Chang, Michael Collins

    Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 1496–1500

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    Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation

    Melvin Johnson, Mike Schuster, Quoc V. Le, Maxim Krikun, Yonghui Wu, Zhifeng Chen, Nikhil Thorat, Fernanda Viégas, Martin Wattenberg, Greg Corrado, Macduff Hughes, Jeffrey Dean

    Google (2016)

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    Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

    Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, Łukasz Kaiser, Stephan Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, Keith Stevens, George Kurian, Nishant Patil, Wei Wang, Cliff Young, Jason Smith, Jason Riesa, Alex Rudnick, Oriol Vinyals, Greg Corrado, Macduff Hughes, Jeffrey Dean

    CoRR, vol. abs/1609.08144 (2016)

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    Addressing the Rare Word Problem in Neural Machine Translation

    Thang Luong, Ilya Sutskever, Quoc V. Le, Oriol Vinyals, Wojciech Zaremba

    ACL (2015)

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    Efficient Top-Down BTG Parsing for Machine Translation Preordering

    Tetsuji Nakagawa

    Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), Association for Computational Linguistics (2015), pp. 208-218

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    Pushdown automata in statistical machine translation

    Cyril Allauzen, Bill Byrne, Adrià de Gispert, Gonzalo Iglesias, Michael Riley

    Computational Linguistics, vol. 40 (2014), pp. 687-723

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    Enlisting the Ghost: Modeling Empty Categories for Machine Translation

    Bing Xiang, Xiaoqiang Luo, Bowen Zhou

    Proceedings of ACL, ACL (2013), pp. 822-831

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    Exploiting Similarities among Languages for Machine Translation

    Tomas Mikolov, Quoc V. Le, Ilya Sutskever

    ARXIV (2013)

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    Source-Side Classifier Preordering for Machine Translation

    Uri Lerner, Slav Petrov

    Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP '13) (2013)

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    A Class-Based Agreement Model For Generating Accurately Inflected Translations

    Spence Green, John DeNero

    50th Annual Meeting of the Association for Computational Linguistics (ACL 2012)

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    A Systematic Comparison of Phrase Table Pruning Techniques

    Richard Zens, Daisy Stanton, Peng Xu

    Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, Association for Computational Linguistics, Jeju Island, Korea, pp. 972-983

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    Fast and Scalable Decoding with Language Model Look-Ahead for Phrase-based Statistical Machine Translation

    Joern Wuebker, Hermann Ney, Richard Zens

    Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics, Association for Computational Linguistics, Jeju, Republic of Korea (2012), pp. 28-32

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    Unsupervised Translation Sense Clustering

    Mohit Bansal, John DeNero, Dekang Lin

    the North American Association of Computational Linguistics (2012)

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    A Lightweight Evaluation Framework for Machine Translation Reordering

    David Talbot, Hideto Kazawa, Hiroshi Ichikawa

    Proceedings of the 6th Workshop on Statistical Machine Translation (2011), pp. 468-476

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    Binarized Forest to String Translation

    Hao Zhang, Licheng Fang, Peng Xu, Xiaoyun Wu

    ACL (2011), pp. 835-845

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    Hierarchical Phrase-Based Translation Representations

    Gonzalo Iglesias, Cyril Allauzen, William Byrne, Adrià de Gispert, Michael Riley

    Proceedings of EMNLP 2011

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    Inducing Sentence Structure from Parallel Corpora for Reordering

    John DeNero, Jakob Uszkoreit

    Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing (EMNLP), Association for Computational Linguistics

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    Language-independent Compound Splitting with Morphological Operations

    Klaus Macherey, Andrew M. Dai, David Talbot, Ashok C. Popat, Franz Och

    ACL HLT 2011, pp. 10

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    Model-Based Aligner Combination Using Dual Decomposition

    John DeNero, Klaus Macherey

    Proceedings of the Association for Computational Linguistics (ACL), 2011

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    Training a Parser for Machine Translation Reordering

    Jason Katz-Brown, Slav Petrov, Ryan McDonald, Franz Och, David Talbot, Hiroshi Ichikawa, Masakazu Seno

    Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing (EMNLP '11)

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    Translation-Inspired OCR

    Dmitriy Genzel, Ashok C. Popat, Nemanja Spasojevic, Michael Jahr, Andrew Senior, Eugene Ie, Frank Yung-Fong Tang

    ICDAR-2011

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    Watermarking the Outputs of Structured Prediction with an application in Statistical Machine Translation

    Ashish Venugopal, Jakob Uszkoreit, David Talbot, Franz Och, Juri Ganitkevitch

    Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing (EMNLP), Association for Computational Linguistics

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    Automatically Learning Source-side Reordering Rules for Large Scale Machine Translation

    Dmitriy Genzel

    COLING-2010

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    Large Scale Parallel Document Mining for Machine Translation

    Jakob Uszkoreit, Jay Ponte, Ashok Popat, Moshe Dubiner

    Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010), Coling 2010 Organizing Committee, Beijing, China, pp. 1101-1109

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    Model Combination for Machine Translation

    John DeNero, Shankar kumar, Ciprian Chelba, Franz Och

    Proceedings of the North American Chapter of the Association for Computational Linguistics (NAACL) (2010), pp. 975-983

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    Statistical Language Modeling

    Ciprian Chelba

    The Handbook of Computational Linguistics and Natural Language Processing, Wiley-Blackwell, John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ United Kingdom (2010), pp. 74-104

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    Syntax based reordering with automatically derived rules for improved statistical machine translation

    Karthik Visweswariah, Jiri Navratil, Jeffrey Sorensen, Vijil Chenthamarakshan, Nanda Kambhatla

    Proceedings of the 23rd International Conference on Computational Linguistics, Association for Computational Linguistics, Stroudsburg, PA, USA (2010), pp. 1119-1127

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    “Poetic” Statistical Machine Translation: Rhyme and Meter

    Dmitriy Genzel, Jakob Uszkoreit, Franz Och

    EMNLP (2010), pp. 158-166

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    Compiling a massive, multilingual dictionary via probabilistic inference

    Mausam, Stephen Soderland, Oren Etzioni, Daniel S. Weld, Michael Skinner, Jeff Bilmes

    ACL-IJCNLP '09: Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1, Association for Computational Linguistics, Morristown, NJ, USA (2009), pp. 262-270

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    Creating a High-Quality Machine Translation System for a Low-Resource Language: Yiddish

    Dmitriy Genzel, Klaus Macherey, Jakob Uszkoreit

    MT Summit XII (2009)

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    Efficient Minimum Error Rate Training and Minimum Bayes-Risk Decoding for Translation Hypergraphs and Lattices

    Shankar Kumar, Wolfgang Macherey, Chris Dyer, Franz Och

    Proceedings of the 47th Annual Meeting of the ACL and the 4th IJCNLP of the AFNLP, ACL and AFNLP (2009), pp. 163-171

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    Learning linear ordering problems for better translation

    Roy Tromble, Jason Eisner

    EMNLP '09: Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, Morristown, NJ, USA, pp. 1007-1016

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    Using a dependency parser to improve SMT for subject-object-verb languages

    Peng Xu, Jaeho Kang, Michael Ringgaard, Franz Och

    NAACL '09: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Association for Computational Linguistics, Morristown, NJ, USA, pp. 245-253

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    A systematic comparison of phrase-based, hierarchical and syntax-augmented statistical MT

    Andreas Zollmann, Ashish Venugopal, Franz Josef Och, Jay Ponte

    Proceedings of the 22nd International Conference on Computational Linguistics (COLING) (2008)

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    Distributed Word Clustering for Large Scale Class-Based Language Modeling in Machine Translation

    Jakob Uszkoreit, Thorsten Brants

    Proceedings of ACL-08: HLT, Association for Computational Linguistics, Columbus, Ohio (2008), pp. 755-762

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    Lattice Minimum Bayes-Risk Decoding for Statistical Machine Translation

    Roy Tromble, Shankar Kumar, Franz Och, Wolfgang Macherey

    Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, pp. 620-629

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    Lattice-based Minimum Error Rate Training for Statistical Machine Translation

    Wolfgang Macherey, Franz Och, Ignacio Thayer, Jakob Uszkoreit

    Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing (EMNLP), Association for Computational Linguistics, pp. 725-734

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    Mining Parenthetical Translations from the Web by Word Alignment

    Dekang Lin, Shaojun Zhao, Benjamin Van Durme, Marius Pasca

    Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL-2008), Columbus, Ohio, pp. 994-1002

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    Using Word Space Models for Enriching Multilingual Lexical Resources and Detecting the Relation Between Morphological and Semantic Composition

    Adil Toumouh, Dominic Widdows, Ahmed Lehireche

    International Conference on Web and Information Tecnologies (ICWIT '08) (2008), pp. 195-201

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    An Empirical Study on Computing Consensus Translations from Multiple Machine Translation Systems

    Wolfgang Macherey, Franz J. Och

    Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), Association for Computational Linguistics, 209 N. Eighth Street, East Stroudsburg, PA, USA, pp. 986-995

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    Improving Word Alignment with Bridge Languages

    Shankar Kumar, Franz Och, Wolfgang Macherey

    Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, Association for Computational Linguistics, 209 N. Eighth Street, East Stroudsburg, PA, USA (2007)

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    Inversion transduction grammar for joint phrasal translation modeling

    Colin Cherry, Dekang Lin

    SSST '07: Proceedings of the NAACL-HLT 2007/AMTA Workshop on Syntax and Structure in Statistical Translation, Association for Computational Linguistics, Morristown, NJ, USA, pp. 17-24

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    Large Language Models in Machine Translation

    Thorsten Brants, Ashok C. Popat, Peng Xu, Franz J. Och, Jeffrey Dean

    Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), pp. 858-867

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    A path-based transfer model for machine translation

    Dekang Lin

    COLING '04: Proceedings of the 20th international conference on Computational Linguistics, Association for Computational Linguistics, Morristown, NJ, USA (2004), pp. 625

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