TrustRank: inducing trust in automatic translations via ranking

  • Authors:
  • Radu Soricut;Abdessamad Echihabi

  • Affiliations:
  • Language Weaver, Inc., Los Angeles, CA;Language Weaver, Inc., Los Angeles, CA

  • Venue:
  • ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
  • Year:
  • 2010

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Abstract

The adoption of Machine 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.