Comparison of crowdsourcing translation with Machine Translation

Dimitra Anastasiou · Rajat Kumar Gupta

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Translation Studies and Practices Natural Language Processing Techniques Mobile Crowdsensing and Crowdsourcing

Abstract

In this paper we examine the model of crowdsourcing for translation and compare it with Machine Translation (MT). The large volume of material to be translated, the translation of this material into many languages combined with tight deadlines lead enterprises today to follow either crowdsourcing and/or MT. Crowdsourcing translation shares many characteristics with MT, as both can cope with high volume, perform at high speed, and reduce the translation cost. MT is an older technology, whereas crowdsourcing is a new phenomenon gaining much ground over time, mainly through Web 2.0. Examples and challenges of both models will be discussed and the paper is closed with future prospects regarding the combination of crowdsourcing and MT, so that they are not regarded as opponents. These prospects are partially based on the results of a survey we conducted. Based on our background, experience, and research, this paper covers aspects both from the point of view of translation studies and computational linguistics applications as well as of information sciences, and particularly the development of the Web regarding user-generated content.

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2008Harnessing the wisdom of crowds in wikipedia 2015Evolution of User-generated Translation 2008New learning network paradigms: Communities of objectives, crowdsourcing, wikis and open source 2014Electronic Tools for Translators 2006Motivations of contributors to Wikipedia 2010Crowdsourcing: How and Why Should Libraries Do It?2007FANSUBBING ANIME: INSIGHTS INTO THE ‘BUTTERFLY EFFECT’ OF GLOBALISATION ON AUDIOVISUAL TRANSLATION 2010The Translation Crowd

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