This paper proposes a method that leverages multiple machine translation (MT) engines for paraphrase generation (PG). The method includes two stages. Firstly, we use a multi-pivot...
We describe a new unsupervised approach for synonymy discovery by aligning paraphrases in monolingual domain corpora. For that purpose, we identify phrasal terms that convey most ...
In this paper, we study the problem of extracting technical paraphrases from a parallel software corpus, namely, a collection of duplicate bug reports. Paraphrase acquisition is a...
Xiaoyin Wang, David Lo, Jing Jiang, Lu Zhang, Hong...
We present a novel approach to deciding whether two sentences hold a paraphrase relationship. We employ a generative model that generates a paraphrase of a given sentence, and we ...
Lattice decoding in statistical machine translation (SMT) is useful in speech translation and in the translation of German because it can handle input ambiguities such as speech r...
We propose a supervised, two-phase framework to address the problem of paraphrase recognition (PR). Unlike most PR systems that focus on sentence similarity, our framework detects...
This paper presents a method for adapting a language generator to the strengths and weaknesses of a synthetic voice, thereby improving the naturalness of synthetic speech in a spo...
We improve the quality of paraphrases extracted from parallel corpora by requiring that phrases and their paraphrases be the same syntactic type. This is achieved by parsing the E...
In previous work, we presented a preliminary study to identify paraphrases between technical and lay discourse types from medical corpora dedicated to the French language. In this...
Paraphrase detection can be seen as the task of aligning sentences that convey the same information but yet are written in different forms. Such resources are important to automat...