Jack the reader : a machine reading framework

Many Machine Reading and Natural Language Understanding tasks require reading supporting text in order to answer questions. For example, in Question Answering, the supporting text can be newswire orWikipedia articles; in Natural Language Inference, premises can be seen as the supporting text and hypotheses as questions. Providing a set of useful primitives operating in a single framework of related tasks would allow for expressive modelling, and easier model comparison and replication. To that end, we present Jack the Reader (JACK), a framework for Machine Reading that allows for quick model prototyping by component reuse, evaluation of new models on existing datasets as well as integrating new datasets and applying them on a growing set of implemented baseline models. JACK is currently supporting (but not limited to) three tasks: Question Answering, Natural Language Inference, and Link Prediction. It is developed with the aim of increasing research efficiency and code reuse

Jack the Reader - A Machine Reading Framework

Many Machine Reading and Natural Language Understanding tasks require reading supporting text in order to answer questions. For example, in Question Answering, the supporting text can be newswire or Wikipedia articles; in Natural Language Inference, premises can be seen as the supporting text and hypotheses as questions. Providing a set of useful primitives operating in a single framework of related tasks would allow for expressive modelling, and easier model comparison and replication. To that end, we present Jack the Reader (Jack), a framework for Machine Reading that allows for quick model prototyping by component reuse, evaluation of new models on existing datasets as well as integrating new datasets and applying them on a growing set of implemented baseline models. Jack is currently supporting (but not limited to) three tasks: Question Answering, Natural Language Inference, and Link Prediction. It is developed with the aim of increasing research efficiency and code reuse.Comment: Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL 2018), System Demonstration

Sequential Attention: A Context-Aware Alignment Function for Machine Reading

In this paper we propose a neural network model with a novel Sequential Attention layer that extends soft attention by assigning weights to words in an input sequence in a way that takes into account not just how well that word matches a query, but how well surrounding words match. We evaluate this approach on the task of reading comprehension (on the Who did What and CNN datasets) and show that it dramatically improves a strong baseline--the Stanford Reader--and is competitive with the state of the art.Comment: To appear in ACL 2017 2nd Workshop on Representation Learning for NLP. Contains additional experiments in section 4 and a revised Figure

Crowdsourcing Multiple Choice Science Questions

We present a novel method for obtaining high-quality, domain-targeted multiple choice questions from crowd workers. Generating these questions can be difficult without trading away originality, relevance or diversity in the answer options. Our method addresses these problems by leveraging a large corpus of domain-specific text and a small set of existing questions. It produces model suggestions for document selection and answer distractor choice which aid the human question generation process. With this method we have assembled SciQ, a dataset of 13.7K multiple choice science exam questions (Dataset available at http://allenai.org/data.html). We demonstrate that the method produces in-domain questions by providing an analysis of this new dataset and by showing that humans cannot distinguish the crowdsourced questions from original questions. When using SciQ as additional training data to existing questions, we observe accuracy improvements on real science exams.Comment: accepted for the Workshop on Noisy User-generated Text (W-NUT) 201

Army-NASA aircrew/aircraft integration program (A3I) software detailed design document, phase 3

The capabilities and design approach of the MIDAS (Man-machine Integration Design and Analysis System) computer-aided engineering (CAE) workstation under development by the Army-NASA Aircrew/Aircraft Integration Program is detailed. This workstation uses graphic, symbolic, and numeric prototyping tools and human performance models as part of an integrated design/analysis environment for crewstation human engineering. Developed incrementally, the requirements and design for Phase 3 (Dec. 1987 to Jun. 1989) are described. Software tools/models developed or significantly modified during this phase included: an interactive 3-D graphic cockpit design editor; multiple-perspective graphic views to observe simulation scenarios; symbolic methods to model the mission decomposition, equipment functions, pilot tasking and loading, as well as control the simulation; a 3-D dynamic anthropometric model; an intermachine communications package; and a training assessment component. These components were successfully used during Phase 3 to demonstrate the complex interactions and human engineering findings involved with a proposed cockpit communications design change in a simulated AH-64A Apache helicopter/mission that maps to empirical data from a similar study and AH-1 Cobra flight test

Accessible Shopping System for Blind and Visually Impaired Individuals

Self-Dependency of disabled persons is very important in their daily lives. This is a cost effective prototype system that help blind persons to shop independently. This paper presents a camera-based label reader for blind persons to read names of labels on the products. The proposed framework can be classified as image capturing, data processing audio output. In Image capturing web Camera is use to capture the image of object or product packaging and captured image is send to the image processing Platform. In Data processing the image is processed internally and the text will get filtered from the image. Finally, the filtered texts are output to blind users in the form voice. The Tesseract library is used to get the plain text from text region and flite library is used to get audio output. This proposed framework is implemented using Raspberry Pi board

The Birth of Pictoriality in Computer Media

The aim of the paper is to follow some milestones of the story of computer media as far as the notion of pictoriality is concerned. I am going to describe in the most general way how it happens that two quite separate technologies as computer machine and pictorial representation met and since then became almost inseparable

Unless Someone Like You Cares a Whole Awful Lot: Apocalypse as Children’s Entertainment

This article explores an unusual subset of children’s narrative, the apocalyptic environmentalist text, and argues that such texts perform the perverse ideological work of shifting blame for ecological crisis from its perpetrators (the parents’ generation) to its victims (the child who is now called upon to act). These texts transform the drama of innocence and experience that is paradigmatic of children’s narrative by destroying the child’s innocence through their very transmission, by informing them of a dire crisis they then become obliged to repair. The article’s primary examples are Captain Planet, The Lorax, WALL-E and The Butter Battle Book, only the last of which finds a way to clearly articulate crisis without also shifting blame