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1、Session:ToolsforAnalysisFebruary11-15,2012,Seattle,WA,USACollaborativeWorkflowforCrowdsourcingTranslationVamshiAmbati,StephanVogel,JaimeCarbonellLanguageTechnologiesInstitute,CarnegieMellonUniversity5000ForbesAvenue,Pittsburgh,PA15213fvamshi,vogel,jgcg@cs.cmu.eduACMCl
2、assificationKeywordsofbuildingtranslationsystemsformostlanguagescanbesig-K.4.3OrganizationalImpacts:nificantlyreduced.Computer-supportedcollaborativework]Crowdsourcing,atermthathasbeenpopularizedrecently,istheprocessoffarmingouttaskstoalargeuserpopulationonGeneralTerms
3、theInternet.ThesetasksbroadlybelongtothelanguageorDesign;HumanFactors.visioncommunity,whereforanumberoftasksitiseitherimpossibleorchallengingandtime-consumingforcomput-AuthorKeywordserstocompletethem,whereasonlyrequiresafewsecondsLanguagetranslation,Collaborativework
4、flow,forahumantocomplete.Forexample,identifyingapersonCrowdsourcing,AmazonMechanicalTurkinaphotograph,taggingavideoforaparticularevent,flag-ginganemailasspam,identifyingthesentimentofawrit-ABSTRACTtentext,spottingcharactersinanimagearestillsomeoftheInthispaper,weexplor
5、ethechallengesinvolvedincrowd-challengingresearchproblemstocomputers.WiththeadventofonlinemarketplaceslikeAmazon’sMechanicalTurk1andsourcingthetaskoftranslationovertheweb,whereremotelylocatedtranslatorsworkonprovidingtranslationsindepen-systematicmicro-paymentmechani
6、sms,crowdsourcingisbe-dentofeachother.Wethen,proposeacollaborativeworkflowcomingfeasibleandeasytoconduct.forcrowdsourcingtranslationtoaddresssomeofthesechal-Recentworkhasseenarapidadoptionofcrowdsourcingandlenges.Inourpipelinemodel,thetranslatorsareworkinginMechanical
7、Turkforresearchtasks,especiallyinthelan-phaseswhereoutputfromearlierphasescanbeenhancedinguageprocessingcommunity[9].Inthispaper,weconductthesubsequentphases.WealsohighlightsomeofthenovelallourcrowdsourcingexperimentsonAmazon’sMechani-contributionsofthepipelinemodell
8、ikeassistivetranslationcalTurk.Crowdsourcingtranslationinvolvespostingtasksandtranslationsynthesisthatcanleveragemonolingualandwhic
