The source text provided to a machine translation system is typically only one of many ways the input sentence could have been expressed, and alternative forms of expression can often produce a better translation. We introduce here error driven paraphrasing of source sentences: instead of paraphrasing a source sentence exhaustively, we obtain paraphrases for only the parts that are predicted to...

We propose a novel approach to translating from a morphologically complex language. Unlike previous research, which has targeted word inflections and concatenations, we focus on the pairwise relationship between morphologically related words, which we treat as potential paraphrases and handle using paraphrasing techniques at the word, phrase, and sentence level. An important advantage of this f...

Patent specifications consist of patent claims and detailed descriptions. While patent claims are the most important part of patent specifications, they are compositionally or combinationally described and difficult to read. By aligning patent claims with detailed description, the readability of patent claims can be improved because paraphrases for the claims can be found. In this paper, we pro...

A major challenge in paraphrase research is the lack of parallel corpora. In this paper, we present a new method to collect large-scale sentential paraphrases from Twitter by linking tweets through shared URLs. The main advantage of our method is its simplicity, as it gets rid of the classifier or human in the loop needed to select data before annotation and subsequent application of paraphrase...

We address the text-to-text generation problem of sentence-level paraphrasing — a phenomenon distinct from and more difficult than wordor phrase-level paraphrasing. Our approach applies multiple-sequence alignment to sentences gathered from unannotated comparable corpora: it learns a set of paraphrasing patterns represented by word lattice pairs and automatically determines how to apply these p...

Monolingual text-to-text generation is an emerging research area in Natural Language Processing. One reason for the interest in such generation systems is the possibility to automatically learn text-to-text generation strategies from aligned monolingual corpora. In this context, paraphrase detection can be seen as the task of aligning sentences that convey the same information but yet are writt...

Abstract Automatic paraphrase generation is an essential task of natural language processing. However, due to the scarcity corpus in many languages, Chinese, for example, generating high-quality paraphrases these languages still challenging. Especially domain paraphrasing, it even more difficult obtain in-domain sentence pairs. In this paper, we propose a novel approach domain-specific zero-sho...

In this work, we present a scenario where contextual targeted paraphrasing of sub-sentential phrases is performed automatically to support the task of text revision. Candidate paraphrases are obtained from a preexisting repertoire and validated in the context of the original sentence using information derived from the Web. We report on experiments on French, where the original sentences to be r...