Machine comprehension (MC), answering a query about a given context paragraph, requires modeling complex interactions between the context and the query. Recently, attention mechanisms have been successfully extended to MC. Typically these methods use attention to focus on a small portion of the context and summarize it with a fixed-size vector, couple attentions temporally, and/or often form a ...

Recently proposed Story Cloze Test [Mostafazadeh et al., 2016] is a commonsense machine comprehension application to deal with natural language understanding problem. This dataset contains a lot of story tests which require commonsense inference ability. Unfortunately, the training data is almost unsupervised where each context document followed with only one positive sentence that can be infer...

Recent work has suggested that the current “breed” of privacy policy represents a significant challenge in terms of comprehension to the average Internet-user. Due to display limitations, it is easy to represent the conjecture that this comprehension level should drop when these policies are moved into a mobile environment. This paper explores the question of how much does comprehension decreas...

An open-source rule-based machine translation system is developed for Scots, a low-resourced minor language closely related to English and spoken in Scotland and Ireland. By concentrating on translation for assimilation (gist comprehension) from Scots to English, it is proposed that the development of dictionaries designed to be used within the Apertium platform will be sufficient to produce tr...

The intent of the study was to find out whether raters possessing certain characteristics might be better at predicting speech in general, using the cloze procedure, and also whether some raters might be better at predicting certain types of speech (alcoholic vs. schizophrenic speech). 279 raters were characterized in terms of IS variables, including 7 socioeconomic characteristics and 6 verbal...

This paper describes two supervised baseline systems for the Story Cloze Test Shared Task (Mostafazadeh et al., 2016a). We first build a classifier using features based on word embeddings and semantic similarity computation. We further implement a neural LSTM system with different encoding strategies that try to model the relation between the story and the provided endings. Our experiments show...

This study attempts to explore the effects of formal schemata or rhetorical patterns on reading comprehension through detailed analysis of a case study of 45 non-English majors from X University. The subjects were selected from three classes of comparable English level and were divided into three groups. Each group was asked to recall the text and finish a cloze test after reading one of three ...

Four experiments examined participants' ability to produce surface characteristics of sentences using an on-line story reading task. Participants read a series of stories in which either all, or the majority of sentences were written in the same "style," or surface form. Twice per story, participants were asked to fill in a blank consistent with the story. For sentences that contained three sty...

The multiple choice cloze (MCC) question format is commonly used to assess students' comprehension. It is an especially useful format for ITS because it is fully automatable and can be used on any text. Unfortunately, very little is known about the factors that influence MCC question difficulty and student performance on such questions. In order to better understand student performance on MCC q...