Within the field of computational linguistics, recent research has made successful advances in integrating word space models with n-gram models. This is of particular interest when a model that encapsulates both semantic and syntactic information is desirable. A potential application for this can be found in the field of psycholinguistics, where the neural response N400 has been found to occur ...

The present study investigated simultaneous processing of language and music using visually presented sentences and auditorily presented chord sequences. Music-syntactically regular and irregular chord functions were presented synchronously with syntactically correct or incorrect words, or with words that had either a high or a low semantic cloze probability. Music-syntactically irregular chord...

Software readability and comprehension are important factors in software maintenance. There is a large body of research on software measurement, but the actual factors that make software easier to read or easier to comprehend are not well understood. In the present study, we investigate the role of method chains and code comments in software readability and comprehension. Our analysis comprises...

Ten participants learned a miniature language (Anigram), which they later employed to verbally describe a pictured event. Using magnetoencephalography, the cortical dynamics of sentence production in Anigram was compared with that in the native tongue from the preparation phase up to the production of the final word. At the preparation phase, a cartoon image with two animals prompted the partic...

Reading in a second language (L2) is complex process that incorporates linguistic knowledge and literacy abilities, as well strategic competence to approach different types of reading tasks depending on goals. However, much the previous research was limited correlational studies focused relative contribution broad categories L2 proficiency first-language (L1) comprehension. investigations into ...

Abstract In order to have a better understanding of the nature reading behavior, it is quite essential scrutinize underlying assumptions two competing theories: componential approach and unitary hypothesis see how this reflected on testing skills. As result, current study was aimed at broadening existing knowledge horizon by trying identify if there relationship in overall scores learners diffe...

We propose a novel neural attention architecture to tackle machine comprehension tasks, such as answering Cloze-style queries with respect to a document. Unlike previous models, we do not collapse the query into a single vector, instead we deploy an iterative alternating attention mechanism that allows a fine-grained exploration of both the query and the document. Our model outperforms state-of...

A significant number of neural architectures for reading comprehension have recently been developed and evaluated on large cloze-style datasets. We present experiments supporting the emergence of “predication structure” in the hidden state vectors of these readers. More specifically, we provide evidence that the hidden state vectors represent atomic formulas Φ[c] where Φ is a semantic property ...

We present a resource-lean neural recognizer for modeling coherence in commonsense stories. Our lightweight system is inspired by successful attempts to modeling discourse relations and stands out due to its simplicity and easy optimization compared to prior approaches to narrative script learning. We evaluate our approach in the Story Cloze Test1 demonstrating an absolute improvement in accura...