Paper: Introduction of a new paraphrase generation tool based on Monte-Carlo sampling

ACL ID P09-2063
Title Introduction of a new paraphrase generation tool based on Monte-Carlo sampling
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2009
Authors

We propose a new specifically designed method for paraphrase generation based on Monte-Carlo sampling and show how this algorithm is suitable for its task. Moreover, the basic algorithm presented here leaves a lot of opportunities for future improvement. In particular, our algorithm does not constraint the scoring function in opposite to Viterbi based decoders. It is now possible to use some global features in paraphrase scoring functions. This algorithm opens new outlooks for paraphrase generation and other natural language processing applications like statistical tical machine translation.