Structure identification has been used widely in many contexts. Grammatical Learning methods are used to find structure information through sequences. Due to negative results, alternative representations have to be used for Grammatical Learning. One such representation is recurrent neural network. Recurrent neural networks are proposed as extended automata. In this chapter, we first summarize r...

Detection and correction of Chinese grammatical errors have been two of major challenges for Chinese automatic grammatical error diagnosis. This paper presents an N-gram model for automatic detection and correction of Chinese grammatical errors in NLPTEA 2017 task. The experiment results show that the proposed method is good at correction of Chinese grammatical errors.

This research aims to identify the common errors in reading Arabic texts among students and their causes. As for method, researcher used a descriptive analytical method. Observation, interview, documentation were collect data. After carried out scientific research, I found that mistakes of learner are divided into two types, namely, grammatical morphological errors. Grammatical most frequent te...

Fossilization has become the focus of many L2 studies since its introduction in 1972 as many learners fail to achieve native-speaker competence. Researchers have tried to unravel the causes of fossilization, among which noticing has been claimed to be of great importance. This  study  aimed  to  explore  the  effect  of  noticing  on  fossilization.  To  achieve  this  aim,  a mixed-methods app...

PURPOSE This study investigated the level of grammatical accuracy in typically developing 3-year-olds and the types of errors they produce. METHOD Twenty-two 3-year-olds participated in a picture description task. The percentage of grammatical utterances was computed and error types were analyzed. RESULTS The mean level of grammatical accuracy in typical 3-year-olds was ∼71%, with a wide ra...

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 ...