acl acl2010 acl2010-244 acl2010-244-reference knowledge-graph by maker-knowledge-mining
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Author: Radu Soricut ; Abdessamad Echihabi
Abstract: The adoption ofMachine Translation technology for commercial applications is hampered by the lack of trust associated with machine-translated output. In this paper, we describe TrustRank, an MT system enhanced with a capability to rank the quality of translation outputs from good to bad. This enables the user to set a quality threshold, granting the user control over the quality of the translations. We quantify the gains we obtain in translation quality, and show that our solution works on a wide variety of domains and language pairs.
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