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1. Using Monolingual Crowds to Improve Translation. Source Language. Target Language. MT. Sentence. Sentence. Crowd Tasks:. 1. 1. Vote. Vote. MT and word alignment. 2. 2. Identify error spans. Paraphrase. Crowd Tasks:. 3. 3. Explain errors. Create new translation
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1 Using Monolingual Crowds toImprove Translation Source Language Target Language MT Sentence Sentence Crowd Tasks: 1 1 Vote Vote MT and word alignment 2 2 Identify error spans Paraphrase Crowd Tasks: 3 3 Explain errors Create new translation candidates Yakov Kronrod1, Chang Hu2, Olivia Buzek2, Alex Quinn2University of Maryland (1) Dept. of Linguistics (2) Dept. of Computer Science New candidate 1 … 2 3 repeat … Space of Available Translation Options • ParaTrans: Targeted Paraphrasing • Monolingual speakers improving translation quality • Human participants perform the following tasks: • Identify mistranslated spans in target language • Create paraphrases for spans in source language responsible for the target error spans. • Produces gains of 0.82 and 1.32 for adequacy and fluency on a 5-point scale • Improves 65.3% of sentences examined • Yields increases of +0.9 BLEU to +3.8 BLEU, depending on size of error span, in an oracle study. Monolingual Human Participation Affordability Quality Paraphrases from the Crowd Translations and Human Judgments Original Google Translate output (GT), with translations produced by the targeted paraphrase translation process (TP), selected to show a range from strong to weak improvements in fluency. Fluency and adequacy (preservation of meaning) were rated on a 5-point scale by independent judges not familiar with this research. The Bigger Picture: MonoTrans Features Results • Online system for collaborative monolingual translation • Asynchronous edits, shorttasks, minimal context 68% of sentences translated perfectly with no bilingual humans UMD HCI Lab (cs.umd.edu/hcil) Comp. Ling. and Info. Processing Lab (umiacs.umd.edu/labs/clip) MonoTrans Project Page: (http://www.cs.umd.edu/hcil/monotrans)