Abstract:

The report will start with the term ‘crowdsourcing’ definition and mention that the concept (crowd+sourcing) was coined in 2006 by Jeff Howe. It is necessary to underline that there has been a rise in Crowdsourcing Translation recently, the examples include Cross-Lingual Wiki Engine (content translation that do not rely on professional translators), Microsoft (crowdsource editing of machine translation of their knowledge base), Geni.com (crowdsource language translations of the site to volunteers), etc. Further on the report will provide brief analysis of crowd sourcing translation examples revealing that the above practice involves machine translation engine and human post-editing of machine translation output by bilinguals.
As far as the language and translation skills training is concerned crowdsourcing translation phenomenon might be interesting as today the respective practice involves different tools. Some of them are to be introduced.
For instance, there are specialized sources for concrete language pairs translation practice; thus, Meedan use an English-Arabic machine translation engine and human post-editing of machine translation output by bilinguals, Yeeyan.org invites registered users to collectively translate news articles from English to Chinese, Asia Online use bilingual surfers to edit machine translation output initially post-edited by staff linguists of this company.
Meanwhile other tools focus on dictionaries building and development. For instance Wordreference is an engine that provides free online bilingual dictionaries and tools, covers over 10 language pairs.Lingua project offers opportunities for traineeships for students in translation or modern languages. Duolingo was created by Luis von Ahn in 2011, as ‘a free language-learning website and crowdsourced text translation platform, has already translated 24 000 sentences, has didactic potential as users progress through the lessons they simultaneously help to translate websites and other documents. Projects that involved crowd sourcing for legal translation will be paid a special attention (Eu sponsored Citzalia project) as they have synergy value for human rights, language and culture mediation, social subcultures development, etc. Basing on the above crowdsourcing examples the report will prove that crowdsourcing is a step beyond existing language training practice as there is interaction between machine translation and crowdsourcing, the text is machine-translated and can then be improved and revised by the user. What is more human crowdsourced translation has its privilege over the raw machine translation (that can help a user understand what the information is about but does not contribute to a foreign culture understanding).
Crowdsourcing shifts the focus from translation itself onto the post-editors’ function, quality control and terminological search and polishing. Crowdsourcing proves that there will always be documents that require professional translation services (confidential documents, highly specialized legal and medical texts, etc) in the above fields crowdtranslation is not enough as human lives can be affected and damaged.
Further on the report will specify the innovative teaching model based on crowd sourcing translation integration intotranslation skills collaborative learning environment. Special emphasis will be laid on crowdsourcing technology-based assignments for legal translation skills training.

Keywords:

Legal translation, crowdsourcing translation, ICT tools for translation.