The enhancement of machine translation for low-density languages using Web-gathered parallel texts.

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The majority of the world's languages are poorly represented in informational media like radio, television, newspapers, and the Internet. Translation into and out of these languages may offer a way for speakers of these languages to interact with the wider world, but current statistical machine translation models are only effective with a large corpus of parallel texts - texts in two languages that are translations of one another - which most languages lack. This thesis describes the Babylon project which attempts to alleviate this shortage by supplementing existing parallel texts with texts gathered automatically from the Web -- specifically targeting … continued below

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Mohler, Michael Augustine Gaylord December 2007.

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  • Mohler, Michael Augustine Gaylord

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The majority of the world's languages are poorly represented in informational media like radio, television, newspapers, and the Internet. Translation into and out of these languages may offer a way for speakers of these languages to interact with the wider world, but current statistical machine translation models are only effective with a large corpus of parallel texts - texts in two languages that are translations of one another - which most languages lack. This thesis describes the Babylon project which attempts to alleviate this shortage by supplementing existing parallel texts with texts gathered automatically from the Web -- specifically targeting pages that contain text in a pair of languages. Results indicate that parallel texts gathered from the Web can be effectively used as a source of training data for machine translation and can significantly improve the translation quality for text in a similar domain. However, the small quantity of high-quality low-density language parallel texts on the Web remains a significant obstacle.

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  • December 2007

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  • May 2, 2008, 3:16 p.m.

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  • Jan. 21, 2014, 1:44 p.m.

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Mohler, Michael Augustine Gaylord. The enhancement of machine translation for low-density languages using Web-gathered parallel texts., thesis, December 2007; Denton, Texas. (https://digital.library.unt.edu/ark:/67531/metadc5140/: accessed July 17, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; .

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