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    • Habash, Nizar (5)
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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 5 of 5 1 Handling Translation Divergences in Generation-Heavy Hybrid Machine Translation Habash, Nizar; Dorr, Bonnie In: DTIC (2002) BASE Show details 2 Improved Word-Level Alignment: Injecting Knowledge about MT Divergences Dorr, Bonnie J.; Pearl, Lisa; Hwa, Rebecca... In: DTIC (2002) BASE Show details 3 Handling Translation Divergences: Combining Statistical and Symbolic Techniques in Generation-Heavy Machine Translation Habash, Nizar; Dorr, Bonnie In: DTIC (2002) BASE Show details 4 Handling Translation Divergences: Combining Statistical and Symbolic Techniques in Generation-Heavy Machine Translation Habash, Nizar; Dorr, Bonnie. - 2002 Abstract: This paper describes a novel approach to handling translation divergences in a Generation-Heavy Hybrid Machine Translation (GHMT) system.The translation divergence problem is usually reserved for Transfer and Interlingual MT because it requires a large combination of complex lexical and structural mappings. A major requirement of these approaches is the accessibility of large amounts of explicit symmetrical knowledge for both source and target languages. This limitation renders Transfer and Interlingual approaches ineffective in the face of structurally-divergent language pairs with asymmetrical resources. GHMT addresses the more common form of this problem, ource-poor/target-rich, by fully exploiting symbolic and statistical target-language resources. This is accomplished by using target-language lexical semantics, categorial variations and subcategorization frames to overgenerate multiple lexico-structural variations from a target-glossed syntactic dependency of the source-language sentence. The symbolic overgeneration, which accounts for different possible translation divergences, is constrained by a statistical target-language model. (Also LAMP-TR-088) (Also UMIACS-TR-2002-49) URL: http://hdl.handle.net/1903/1202 BASE Hide details 5 Handling Translation Divergences in Generation-Heavy Hybrid Machine Translation Dorr, Bonnie; Habash, Nizar. - 2002 BASE Show details

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