Automatic evaluation of translation quality has proved to be useful when the target language is English. In this paper the evaluation of translation into Japanese is studied. An existing method based on n-gram similarity between translations and reference sentences is difficult to apply to the evaluation of Japanese because of the agglutinativeness and variation of semantically similar expressi...

Digital fingerprinting becomes paid growing attention as a technology resolving copyright problems. Previously, researchers have been only interested in image based digital fingerprinting where secret information is hidden in images, and text have not been the main target of hiding information. In this paper, we propose an information hiding method for text. Our information hiding method is bas...

We argue in this paper that sophisticated mi-croplanning techniques are required even for mathematical proofs, in contrast to the belief that mathematical texts are only schematic and mechanical. We demonstrate why paraphrasing and aggregation signiicantly enhance the exibility and the coherence of the text produced. To this end, we adopted the Text Structure of Meteer as our basic representati...

A central challenge in semantic parsing is handling the myriad ways in which knowledge base predicates can be expressed. Traditionally, semantic parsers are trained primarily from text paired with knowledge base information. Our goal is to exploit the much larger amounts of raw text not tied to any knowledge base. In this paper, we turn semantic parsing on its head. Given an input utterance, we...

We present a new approach to harvesting a large-scale, high quality image-caption corpus that makes a better use of already existing web data with no additional human efforts. The key idea is to focus on Déjà Image-Captions: naturally existing image descriptions that are repeated almost verbatim – by more than one individual for different images. The resulting corpus provides association struct...

This paper proposes a novel method that exploits multiple resources to improve statistical machine translation (SMT) based paraphrasing. In detail, a phrasal paraphrase table and a feature function are derived from each resource, which are then combined in a log-linear SMTmodel for sentence-level paraphrase generation. Experimental results show that the SMT-based paraphrasing model can be enhan...

We discuss the potentialities of structural matching as a compromise between fully-conceptual deep processing approaches and shallow bag-of-words approaches to answer seeking. We extended Collins's Tree Kernel [1] to formulate a new algorithm for soft structural matching, and we also developed and tested a method for combing structural matching with paraphrasing. Unfortunately, we found no posi...

A new approach for Interactive Machine Translation where the author interacts during the creation or the modification of the document is proposed. The explanation of an ambiguity or an error for the purposes of correction does not use any concepts of the underlying linguistic theory : it is a reformulation of the erroneous or ambiguous sentence. The interaction is limited to the analysis step o...

We present a work on detection of manual paraphrasing in documents in comparison with a set of source documents. Manual paraphrasing is a realistic type of plagiarism, where the obfuscation is introduced manually in documents. We have used PAN-PC-10 data set to develop and evaluate our algorithm. The proposed approach consists of two steps, namely, identification of probable plagiarized passage...

This paper describes Parmesan, our submission to the 2014 Workshop on Statistical Machine Translation (WMT) metrics task for evaluation English-to-Czech translation. We show that the Czech Meteor Paraphrase tables are so noisy that they actually can harm the performance of the metric. However, they can be very useful after extensive filtering in targeted paraphrasing of Czech reference sentence...