Computational Grammars can be adapted to detect ungrammatical sentences, effectively transforming them into error detection (or correction) systems. In this paper we provide a theoretical account of how adapt implemented HPSG grammars for grammatical detection. We discuss single input reconstructed in multiple ways and, turn, used specific, high-quality feedback language learners. then move on ...

Effects of negative input for 13 categories of grammatical error were assessed in a longitudinal study of naturalistic adult-child discourse. Two-hour samples of conversational interaction were obtained at two points in time, separated by a lag of 12 weeks, for 12 children (mean age 2;0 at the start). The data were interpreted within the framework offered by Saxton’s (1997; 2000) contrast theor...

The present study was an attempt to provide a psycholinguistic account of cognitive processes underlying responding and questioning. It also strived to identify the potential differences between responding and questioning cognitive processes in Target Language Use Situation tasks. To accomplish the objectives, 65 Iranian general IELTS applicants from two foreign language learning instit...

In this paper we present a Neural Network (NN) architecture for detecting grammatical errors in Statistical Machine Translation (SMT) using monolingual morpho-syntactic word representations in combination with surface and syntactic context windows. We test our approach on two language pairs and two tasks, namely detecting grammatical errors and predicting overall post-editing effort. Our result...