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Collaborative translation

What is it?

Collaborative and social networking technologies, as seen on sites like Wikipedia, Facebook and Amazon Mechanical Turk, are having profound effects in many spheres of human activity. Translation is no exception, as evidenced by Facebook's use of crowdsourcing technology, to co-opt its loyal user base into translating the system's user interface for free. Using this approach, Facebook was able to rapidly recruit 250,000 volunteers, who translated 350,000 words into 70 languages, often with very short lead time (less than two days for high density languages like French) (Baer, 2010).

The Facebook approach is only one of several ways in which massive online collaboration can be leveraged for translation. Other possible uses of collaborative technologies in translation include the following.

  • Agile translation teamware: wiki-like systems and processes that allow multidisciplinary teams of professionals (translators, terminologists, domain experts, revisers, managers) to collaborate on large translation projects, using an agile, grassroot, parallelized process instead of the more top-down, linear assembly-line approach found in most translation workflow systems (ex: Calvert, 2010, Yahaya, 201, Rennato's paper).
  • Collaborative terminology resources: Wikipedia-like platforms for the creation and maintenance of large terminology resources by a crowd of translators, terminologists, domain experts, and even general members of the public (ex: Wiktionary, Kudoz, Urban Dictionary, etc).
  • Translation Memory sharing: platforms for large scale pooling and sharing of multilingual parallel corpora between organizations and individuals (ex: TAUS TM sharing platform, MyMemory, Google Translator Toolkit).
  • Online marketplaces for translators: eBay-like, disintermediated environments for connecting customers and translators directly, with minimal intervention by a middle man (ex: ProZ, Translated.net, TranslatorCafe).
  • Translation crowdsourcing: Mechanical Turk style systems for splitting translation projects into small chunks, and distributing them across large crowds of mostly amateur translators (ex: Facebook, Haiti Relief). This kind of approach can also be used for large scale collection of linguistic data for research purposes or machine translation training (ex: Ambati and Vogal, 2010; Bloodgood and Callison-Burch, 2010)
  • Post-editing by the crowd: systems allowing a large crowd of mostly amateurs to correct the output of machine translations systems, to suggest better translations (ex: Asia Online's Wikipedia project, Google Translate's "Contribute a better translation" feature, Microsoft's Collaborative Translation Framework).


As can be seen from the above list, collaborative translation represents a rich envelope of possibilities which is very complex, varied and still poorly understood. Determining which kind of approach can be used in which contexts and to what effect is still somewhat of a black art, and trial and error is often the only way to find out. The web site you are currently visiting is a collaboratively built repository of best-practices written by seasoned users user these various collaborative translation approaches.

References

Ambati , V.; Vogel S. "Can Crowds Build Parallel Corpora for Machine Translation Systems?", Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk, Los Angeles, California, June 2010.

Baer, N.,"Trends in Crowdsourcing: Case Studies from Not-for-Profit and For-Profit Organisations", ATA 2010, Oct 27-30, 2010, Denver, Colorado, USA (http://www.wiki-translation.com/tiki-download_wiki_attachment.php?attId=62)

Beninatto, R.; De Palma, D. A. "Collaborative Translation", Multilingual, 2008 Resource Directory & Index 2008 (http://www.scribd.com/doc/4069269/Structuring-Collaborative-Translation-20-Less-Delivery-Time-Better-Quality)

Bloodgood, M.; Callison-Burch, C. "Using Mechanical Turk to Build Machine Translation Evaluation Sets", Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk, Los Angeles, California, June 2010.

Calvert, D., "Wiki behind the Firewall: Microscale Online Collaboration in a Translation Agency", ASLIB Translating and the Computer 30, Nov 27-28, 2008, London, UK.

Ellis, D. "A Case Study in Community-Driven Translation of a Fast-Changing Website.", in Internationalization, Design and Global Development Lecture Notes in Computer Science, 2009, Volume 5623/2009, 236-244, DOI: 10.1007/978-3-642-02767-3_26

Munro, R. "Crowdsourced translation for emergency response in Haiti: the global collaboration of local knowledge", in proc. of Collaborative Translation: technology, crowdsourcing, and the translator perspective, AMTA 2010, Oct 31, 2010, Denver, Colorado, USA. (http://www.wiki-translation.com/tiki-download_wiki_attachment.php?attId=63)

Orr Priebe, S. "Tom Sawyer: A crowdsourcing pioneer?", TCWorld, November 2009.

Surowiecki, J, "The Wisdom of Crowds", Anchor, August 16, 2005, ISBN-13: 978-0385721707.

Yahaya, F., "Managing Complex Translation Projects Through Virtual Spaces: a Case Study", ASLIB Translating and the Computer 30, Nov 27-28, 2008, London, UK.

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