Improving Translation via Targeted Paraphrasing

Targeted paraphrasing is a new approach to the problem of obtaining cost-effective, reasonable quality translation that makes use of simple and inexpensive human computations by monolingual speakers in combination with machine translation. The key insight behind the process is that it is possible to spot likely translation errors with only monolingual knowledge of the target language, and it is possible to generate alternative ways to say the same thing (i.e. paraphrases) with only monolingual knowledge of the source language. Evaluations demonstrate that this approach can yield substantial improvements in translation quality.

• Type: Journal
• Year: 2010
• Where: EMNLP
• Authors: Philip Resnik, Olivia Buzek, Chang Hu, Yakov Kronrod, Alexander J. Quinn, Benjamin B. Bederson
• Keywords: EMNLP 2010, Likely Translation Errors, Monolingual Knowledge, Natural Language Processing, Reasonable Quality Translation