Text generation is increasingly common but often requires manual post-editing where high precision is critical to end users. However, manual editing is expensive so we want to ensure this effort is focused on high-value tasks. And we want to maintain stylistic consistency, a particular challenge in crowd settings. We present a case study, analysing human post-editing in the context of a templat...

We present Mask-guided Generative Adversarial Network (MagGAN) for high-resolution face attribute editing, in which semantic facial masks from a pre-trained parser are used to guide the fine-grained image editing process. With introduction of mask-guided reconstruction loss, MagGAN learns only edit parts that relevant desired changes, while preserving attribute-irrelevant regions (e.g., hat, sc...

The goal of our work is to help radiologists remove obscuring structures from a large volume of computed tomography angiography (CTA) images by editing a small number of sections prior to three-dimensional (3D) reconstruction. We combine automated segmentation of the entire volume with manual editing of a small number of sections. The segmentation process uses a neural network to learn threshol...

Text coherence evaluation becomes a vital and lovely task in Natural Language Processing subfields, such as text summarization, question answering, text generation and machine translation. Existing methods like entity-based and graph-based models are engaging with nouns and noun phrases change role in sequential sentences within short part of a text. They even have limitations in global coheren...

Image editing systems are essentially pixel-based. In this paper we propose a novel method for image editing in which the primitive working unit is not a pixel but an edge. The feasibility of this proposal is suggested by recent work showing that a grey-scale image can be accurately represented by its edge map if a suitable edge model and scale selection method are employed 1]. In particular, a...

This is a working paper on a music typesetting system, Sc E X, which is based on the notion of having music scores described in languages that are easy to be read by musicians and whose texts can easily be modiied by the user's preferred variety of text editor. Along with the architecture of Sc E X, two diierent languages are deened: one for describing voices separately, and the other for descr...

The definition of a Text Base Management System is introduced in terms of software engineering. That gives a basis for discussing practical text administration , including questions on corpus properties and appropriate retrieval criteria. Finally, strategies for the derivation of a word data base from an actual TBMS will be discussed. l. Introduction Textual data are a sort of complex data obje...

We will demonstrate SconeEdit, a new tool for exploring and editing knowledge bases (KBs) that leverages interaction with domain texts. The tool provides an annotated view of user-selected text, allowing a user to see which concepts from the text are in the KB and to edit the KB directly from this Text View. Alongside the Text View, SconeEdit provides a navigable KB View of the knowledge base, ...

Nectar enables users of the MoinMoin collaborative wiki editing environment to conveniently create and view in-text annotations to wiki documents without disturbing the underlying document. It is designed to facilitate online collaboration for traditional classroom learning by allowing authors to lock documents for editing, but still solicit comments online. Nectar has an obvious and easy to le...

Recognising entities in social media text is difficult. NER on newswire text is conventionally cast as a sequence labeling problem. This makes implicit assumptions regarding its textual structure. Social media text is rich in disfluency and often has poor or noisy structure, and intuitively does not always satisfy these assumptions. We explore noise-tolerant methods for sequence labeling and ap...