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...

arabic language is in strong relation with jurisprudence in irans university because the lag number of its refrence written by arabic. there many tasks that is in relation with and erstanding this language important tasks are: necessity of attention to the sentence structure in the jurisprudence text and its task for example :relation within two important part of the structure (relation within ...

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 ...

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 ...