Advertisement

Building Multilingual Language Resources in Web Localisation: A Crowdsourcing Approach

  • Asanka Wasala
  • Reinhard Schäler
  • Jim Buckley
  • Ruvan Weerasinghe
  • Chris Exton
Chapter
Part of the Theory and Applications of Natural Language Processing book series (NLP)

Abstract

Before User Generated Content (UGC) became widespread, the majority of web content was generated for a specific target audience and in the language of that target audience. When information was to be published in multiple languages, it was done using well-established localisation methods. With the growth in UGC there are a number of issues, which seem incompatible with the traditional model of software localisation. First and foremost, the number of content contributors has increased hugely. As a by-product of this development, we are also witnessing a large expansion in the scale and variety of the content. Consequently, the demand for traditional forms of localisation (based on existing language resources, a professional pool of translators, and localisation experts) has become unsustainable. Additionally, the requirements and nature of the type of translation are shifting as well: The more web-based communities multiply in scale, type and geographical distribution, the more varied and global their requirements are. However, the growth in UGC also presents a number of localisation opportunities. In this chapter, we investigate web-enabled collaborative construction of language resources (translation memories) using micro-crowdsourcing approaches, as a means of addressing the diversity and scale issues that arise in UGC contexts and in software systems generally. As the proposed approaches are based on the expertise of human translators, they also address many of the quality issues related to MT-based solutions. The first example we provide describes a client-server architecture (UpLoD) where individual users translate elements of an application and its documentation as they use them, in return for free access to these applications. Periodically, the elements of the system and documentation translated by the individual translators are gathered centrally and are aggregated into an integral translation of all, or parts of, the system that can then be re-distributed to the system’s users. This architecture is shown to feed into the design of a browser extension-based client-server architecture (BE-COLA) that allows for the capturing and aligning of source and target content produced by the ‘power of the crowd’. The architectural approach chosen enables collaborative, in-context, and real-time localisation of web content supported by the crowd and generation of high-quality language resources.

Keywords

Central Server Machine Translation Language Resource User Generate Content Language Pair 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This research is supported by the Science Foundation Ireland (SFI) (Grant 07/CE/I1142) as part of the Centre for Next Generation Localisation (CNGL) at the University of Limerick. The prototype was implemented based on Ingiya and FoxReplace add-ons. The authors would like to thank the authors of and the contributors to the above add-ons. The authors would also like to thank Aram Morera-Mesa for his helpful comments and suggestions.

References

  1. 1.
    Alegria I, Cabezon U, de Betoño UF, Labaka G, Aingeru M, Sarasola K, Zubiaga A (2012) Reciprocal enrichment between basque Wikipedia and machine translation. In: Gurevych I, Kim J (eds) The People’s web meets NLP: collaboratively constructed language resources. Theory and applications of natural language processing. Springer, Berlin/HeidelbergGoogle Scholar
  2. 2.
    Anastasiou D (2011) The impact of localisation on semantic web standards. Eur J ePractice (12):42–52Google Scholar
  3. 3.
    Anastasiou D, Morado-Vázquez L (2010) Localisation standards and metadata. In: Sánchez-Alonso S, Athanasiadis IN (eds) Metadata and semantic research. Communications in computer and information science, vol 108. Springer, Berlin/Heidelberg, pp 255–274. doi:10.1007/978-3-642-16552-8_24Google Scholar
  4. 4.
    Bookstein A (1990) Informetric distributions, part I: unified overview. J Am Soc Inf Sci 41(5):368–375. doi: 10.1002/(sici)1097-4571(199007)41:5 < 368::aid-asi8 > 3.0.co;2-cGoogle Scholar
  5. 5.
    Boxma H (2012) RIGI localization solutions. https://sites.google.com/a/rigi-ls.com/www/home. Cited 1 Apr 2012
  6. 6.
    Brooks D (1998) Language resources and international product strategy. Paper presented at the first international conference on language resources and evaluation (LREC), Granada, Spain, 28–30 May 1998Google Scholar
  7. 7.
    Callison-Burch C (2009) Fast, cheap, and creative: evaluating translation quality using Amazon’s mechanical turk. In: Proceedings of the 2009 conference on empirical methods in natural language processing: volume 1, SingaporeGoogle Scholar
  8. 8.
    Crowston K, Howison J (2005) The social structure of free and open source software development. First Monday 10(2–7). http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/fm/article/view/1207/1127. Cited 20 July 2012
  9. 9.
    Daniel Brandon J (2001) Localization of web content. J Comput Small Coll 17 (2):345–358Google Scholar
  10. 10.
    DePalma DA (2007) Lionbridge announces 2006 results. http://upgrade.globalwatchtower.com/2007/06/lionbridge-2006-results/. Cited 20 Jul 2012
  11. 11.
    DePalma DA (2012) Most content remains untranslated. http://www.tcworld.info/tcworld/translation-and-localization/article/most-content-remains-untranslated/. Cited 02 Apr 2012
  12. 12.
    Dutro C (2012) i18n on rails: a Twitter approach. RailsConf 2012, Austin (Texas), 23–25 Apr 2012. https://github.com/newhavenrb/conferences/wiki/i18n-on-Rails:-A-Twitter-Approach. Cited 23 Aug 2012
  13. 13.
    Exton C, Wasala A, Buckley J, Schäler R (2009) Micro crowdsourcing: a new model for software localisation. Localis Focus 8(1):81–89Google Scholar
  14. 14.
    Exton C, Spillane B, Buckley J (2010) A micro-crowdsourcing implementation: the Babel software project. Localis Focus 9(1):46–62Google Scholar
  15. 15.
    Frimannsson A (2005) Adopting standards based XML file formats in open source localisation. Queensland University of Technology, QueenslandGoogle Scholar
  16. 16.
    Gaspari F (2007) The role of online MT in webpage translation. University of Manchester, ManchesterGoogle Scholar
  17. 17.
    Ghosh RA (1998) Interviews with linus torvalds: what motivates software developers. First Monday 3(3–2). http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/fm/article/viewArticle/583/504. Cited 20 July 2012
  18. 18.
    Gift N, Shand A (2009) Introduction to distributed version control systems. https://www.ibm.com/developerworks/aix/library/au-dist_ver_control. Cited 07 Apr 2009
  19. 19.
    Hann IH, Roberts J, Slaughter S, Fielding R (2002) Why do developers contribute to open source projects? First evidence of economic incentives. In: Meeting challenges and surviving success: 2nd workshop on open source software engineering, international conference on software engineering, OrlandoGoogle Scholar
  20. 20.
    Horvat M (2012) Live website localization. Paper presented at the W3C workshop: the multilingual web – the way ahead, Luxembourg, 15–16 Mar 2012Google Scholar
  21. 21.
    Howe J (2006) The rise of crowdsourcing. Wired 14(6):1–4Google Scholar
  22. 22.
    Internet-World-Stats (2012) World internet usage and population statistics (as per December 31, 2011). Miniwatts marketing group. http://www.internetworldstats.com/stats.htm. Cited 21 Jul 2012
  23. 23.
    Jacobs A (2009) Internet usage rises in China. The New York Times. http://www.nytimes.com/2009/01/15/world/asia/15beijing.html?_r=1. Cited 21 Jul 2012
  24. 24.
    Jarvis J (2009) What Would Google Do? HarperCollins, New YorkGoogle Scholar
  25. 25.
    Jiménez-Crespo MA (2011) To adapt or not to adapt in web localization: a contrastive genrebased study of original and localised legal sections in corporate websites. J Spec Transl 15:2–27Google Scholar
  26. 26.
    Kuznetsov S (2006) Motivations of contributors to Wikipedia. SIGCAS Comput Soc 36(2):1. doi:10.1145/1215942.1215943CrossRefGoogle Scholar
  27. 27.
    Large A, Moukdad H (2000) Multilingual access to web resources: an overview. Program Electron Libr Inf Syst 34(1):43–58. doi:10.1108/EUM0000000006938CrossRefGoogle Scholar
  28. 28.
    Lerner J, Tirole J (2002) Some simple economics of open source. J Ind Econ 50(2):197–234. doi:10.1111/1467-6451.00174CrossRefGoogle Scholar
  29. 29.
    Losse K (2008) Keynote. Paper presented at the LRC XIII: localisation4All, Dublin, Ireland, 2–3 Oct 2008Google Scholar
  30. 30.
    Moorkens J (2011) Translation memories guarantee consistency: truth or fiction? Paper presented at the ASLIB translating and the computer 33, London, UK, 17–18 Nov 2011Google Scholar
  31. 31.
    Morado-Vázquez L, Rey JTd (2011) The relevance of metadata during the localisation process – an experiment. Paper presented at the internacional T3L conference: tradumatica, translation technologies and localization, Universitat Autonoma de Barcelona, Spain, 21–22 June 2011Google Scholar
  32. 32.
    Papineni K, Roukos S, Ward T, Zhu WJ (2002) BLEU: a method for automatic evaluation of machine translation. In: Proceedings of the 40th ACL. Association for Computational Linguistics, Philadelphia, pp 311–318Google Scholar
  33. 33.
    Pink D (2009) The surprising science of motivation. TED conferences, LLC. http://www.ted.com/talks/dan_pink_on_motivation.html. Cited 20 July 2012
  34. 34.
    Raymond ES (1999) The cathedral and the bazaar. Knowl Technol Policy 12(3):23–49. doi:10.1007/s12130-999-1026-0CrossRefGoogle Scholar
  35. 35.
    Raymond ES (2001) The cathedral and the bazaar: musings on Linux and open source by an accidental revolutionary. O’Reilly, Beijing/CambridgeGoogle Scholar
  36. 36.
    Rickard J (2009) Translation in the community. Paper presented at the LRC XIV: localisation in the cloud, Limerick, Ireland, 24–25 Sept 2009Google Scholar
  37. 37.
    Sargent BB (2012) ROI lifts the long tail of languages in 2012. Common Sense Advisory, Inc. http://www.commonsenseadvisory.com/AbstractView.aspx?ArticleID=2899. Cited 20 July 2012
  38. 38.
    Schäler R (1994) A practical evaluation of an integrated translation tool during a large scale localisation project. In: The 4th conference on applied natural language processing (ANLP-94), Stuttgart, GermanyGoogle Scholar
  39. 39.
    Schäler R (2010) Localization and translation. In: Handbook of translation studies, vol 1. John Benjamins Publishing Company, Amsterdam/Philadelphia, pp 209–214Google Scholar
  40. 40.
    Schäler R (2012) Information sharing across languages. In: Computer-mediated communication across cultures: international interactions in online environments. IGI Global, Hershey, pp 215–234. doi: 10.4018/978-1-60960-833-0.ch015
  41. 41.
    Schäler R (2012) Introducing social localisation. Paper presented at the workshop, localization world, Silicon ValleyGoogle Scholar
  42. 42.
  43. 43.
    Shannon P (2000) Including language in your global strategy for B2B E-commerce. http://www.worldtradewt100.com/articles/print/83222. Cited 24 Apr 2012
  44. 44.
    Stengers H, Troyer OD, Baetens M, Boers F, Mushtaha AN (2004) Localization of web sites: is there still a need for it? Paper presented at the international workshop on web engineering (held in conjunction with the ACM HyperText 2004 conference), Santa Cruz, USAGoogle Scholar
  45. 45.
    Valverde S, Theraulaz G, Gautrais J, Fourcassie V, Sole RV (2006) Self-organization patterns in wasp and open source communities. Intell Syst IEEE 21(2):36–40. doi:10.1109/mis.2006.34CrossRefGoogle Scholar
  46. 46.
    Wasala A, Weerasinghe R (2008) EnSiTip: a tool to unlock the English web. Paper presented at the 11th international conference on humans and computers, Nagaoka University of Technology, Japan, 20–23 Nov 2008Google Scholar
  47. 47.
    Wikipedia (2012) Wikipedia statistics. http://stats.wikimedia.org/EN/Sitemap.htm. Cited 28 Aug 2012
  48. 48.
    WorldLingo (2000) Increase global sales with WorldLingo. http://www.worldlingo.com/en/company/pr/pr20000223_02.html. Cited 24 Apr 2012
  49. 49.
    Zeitlyn D (2003) Gift economies in the development of open source software: anthropological reflections. Res Policy 32(7):1287–1291CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Asanka Wasala
    • 1
  • Reinhard Schäler
    • 1
  • Jim Buckley
    • 1
  • Ruvan Weerasinghe
    • 2
  • Chris Exton
    • 1
  1. 1.Localisation Research Centre/Centre for Next Generation Localisation, Department of Computer Science and Information SystemsUniversity of LimerickLimerickIreland
  2. 2.University of Colombo School of ComputingColomboSri Lanka

Personalised recommendations