Paper: Improving Multilingual Summarization: Using Redundancy In The Input To Correct MT Errors

ACL ID H05-1005
Title Improving Multilingual Summarization: Using Redundancy In The Input To Correct MT Errors
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2005
Authors

In this paper, we use the information re- dundancy in multilingual input to correct errors in machine translation and thus im- prove the quality of multilingual sum- maries. We consider the case of multi- document summarization, where the input documents are in Arabic, and the output summary is in English. Typically, infor- mation that makes it to a summary appears in many different lexical-syntactic forms in the input documents. Further, the use of multiple machine translation systems pro- vides yet more redundancy, yielding dif- ferent ways to realize that information in English. We demonstrate how errors in the machine translations of the input Arabic documents can be corrected by identify- ing and generating from such redundancy, focusing on noun phrases.