tailieunhanh - Báo cáo khoa học: "Introduction of a new paraphrase generation tool based on Monte-Carlo sampling"

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 machine translation. step in SMT. . | Introduction of a new paraphrase generation tool based on Monte-Carlo sampling Jonathan Chevelu1 2 Thomas Lavergne Yves Lepage1 Thierry Moudenc2 1 GREYC université de Caen Basse-Normandie 2 Orange Labs 2 avenue Pierre Marzin 22307 Lannion @ Abstract 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 machine translation. 1 Introduction A paraphrase generation system is a program which given a source sentence produces a different sentence with almost the same meaning. Paraphrase generation is useful in applications to choose between different forms to keep the most appropriate one. For instance automatic summary can be seen as a particular paraphrasing task Barzilay and Lee 2003 with the aim of selecting the shortest paraphrase. Paraphrases can also be used to improve natural language processing NLP systems. Callison-Burch et al. 2006 improved machine translations by augmenting the coverage of patterns that can be translated. Similarly Sekine 2005 improved information retrieval based on pattern recognition by introducing paraphrase generation. In order to produce paraphrases a promising approach is to see the paraphrase generation problem as a translation problem where the target language is the same as the source language Quirk et al. 2004 Bannard and Callison-Burch 2005 . A problem that has drawn less attention is the generation step which corresponds