This paper describes a project currently under way at SAP dealing with the task of post-editing MT output. As a concrete result of the project, a standard post-editing guide to be used by translator end users is currently being created. The purpose of this post-editing guide is not only to train and support translators in the daily work with MT but also to make the post-editing task more access...

In this paper we investigate the relationship between bimanual (two handed) manipulation and the cognitive theories of task integration, divided attention and epistemic action. We explore these relationships by means of an empirical study based on a curve editing task. This task was designed on the principle of integrating the visual, conceptual and input device space domain of each hand's indi...

Following upon the last year’s CUNI system for automatic post-editing of machine translation output, we focus on exploiting the potential of sequence-to-sequence neural models for this task. In this system description paper, we compare several encoder-decoder architectures on a smaller-scale models and present the system we submitted to WMT 2017 Automatic Post-Editing shared task based on this ...

RNA editing is a posttranscriptional modification that can lead to a change in the encoded protein sequence of a gene. Although a few cases of mammalian coding RNA editing are known to be functionally important, the vast majority of over 2,000 A-to-I editing sites that have been identified from the coding regions of the human genome are likely nonadaptive, representing tolerable promiscuous tar...

Understanding movies and their structural patterns is a crucial task in decoding the craft of video editing. While previous works have developed tools for general analysis, such as detecting characters or recognizing cinematography properties at shot level, less effort has been devoted to understanding most basic edit, Cut. This paper introduces Cut type recognition task, which requires modelin...

This paper describes the Post-Editor Z system submitted to the L2 writing assistant task in SemEval-2014. The aim of task is to build a translation assistance system to translate untranslated sentence fragments. This is not unlike the task of post-editing where human translators improve machine-generated translations. Post-Editor Z emulates the manual process of post-editing by (i) crawling and...

  One of the most problematic areas in foreign language learning is collocation. It is often seen as arbitrary and an overwhelming obstacle to the achievement of nativelike fluency. Current second language (L2) instruction research has encouraged the use of collaborative output tasks in L2 classrooms. This study examined the effects of two types of output tasks (editing and cloze) on the learni...

This paper presents the results of the WMT16 shared tasks, which included five machine translation (MT) tasks (standard news, IT-domain, biomedical, multimodal, pronoun), three evaluation tasks (metrics, tuning, run-time estimation of MT quality), and an automatic post-editing task and bilingual document alignment task. This year, 102 MT systems from 24 institutions (plus 36 anonymized online s...

We introduce a new set of problems based on the Chain Editing problem. In our version of Chain Editing, we are given a set of anonymous participants and a set of undisclosed tasks that every participant attempts. For each participant-task pair, we know whether the participant has succeeded at the task or not. We assume that participants vary in their ability to solve tasks, and that tasks vary ...