id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_rujstqwje5gkdm2bqer4drugey	Ellie Pavlick	The Language Demographics of Amazon Mechanical Turk	2014	14	.pdf	application/pdf	7172	862	67	bilingual parallel corpora in six Indian languages, and use them to train statistical machine translation systems. study by posting 25 sentences to MTurk for Spanish, Chinese, Hindi, Telugu, Urdu, and Haitian Creole. crowdsourcing to construct a 1.5 million word parallel corpus of dialect Arabic and English, training a statistical machine translation system that produced higher quality translations of dialect Arabic We created parallel corpora by translating the 100 most viewed Wikipedia pages in Bengali, Malyalam, Hindi, Tamil, Telugu, and Urdu into Figure 4: Translation quality for languages with at least 50 Turkers. For single word translations, we calculate the quality of translations on the level of individual assignments and aggregated over workers and languages. for the 51 foreign languages that Google Translate covered at the time of the study. Table 3 shows the differences in translation quality when computed using in-region versus out-ofregion Turkers, for the languages with the greatest	./cache/work_rujstqwje5gkdm2bqer4drugey.pdf	./txt/work_rujstqwje5gkdm2bqer4drugey.txt