The foreign learners are not easy to learn Chinese as a second language. Because there are many special rules different from other languages in Chinese. When the people learn Chinese as a foreign language usually make some grammatical errors, such as missing, redundant, selection and disorder. In this paper, we proposed the conditional random fields (CRFs) to detect the grammatical errors. The ...

Five language and tagset independent stochastic taggers, handling morphological and contextual information, are presented and tested in corpora of seven European languages (Dutch, English, French, German, Greek, Italian and Spanish), using two sets of grammatical tags; a small set containing the eleven main grammatical classes and a large set of grammatical categories common to all languages. T...

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...

Grammatical error correction has been an active research area in the field of Natural Language Processing. This paper describes the grammatical error correction system developed at NTHU in participation of the CoNLL-2013 Shared Task. The system consists of four modules in a pipeline to correct errors related to determiners, prepositions, verb forms and noun number. Although more types of errors...

This paper presents an algorithm for dividing Spanish words into syllables. This algorithm is based on grammatical rules which were translated into a simple algorithm, easy to implement and with low computational cost. Experimental results in an evaluation text corpus show an overall error rate of 1.6%. Most of the error is attributed to words with diphthongs and to confusion in the use of pref...

Grammatical error diagnosis is an important task in natural language processing. This paper introduces our Chinese Grammatical Error Diagnosis (CGED) system in the NLP-TEA-3 shared task for CGED. The CGED system can diagnose four types of grammatical errors which are redundant words (R), missing words (M), bad word selection (S) and disordered words (W). We treat the CGED task as a sequence lab...

Studies on grammatical error correction (GEC) have reported the effectiveness of pretraining a Seq2Seq model with large amount pseudodata. However, this approach requires time-consuming for GEC because size In study, we explore utility bidirectional and auto-regressive transformers (BART) as generic pretrained encoder-decoder GEC. With use GEC, can be eliminated. We find that monolingual multil...

Building a system to detect Chinese grammatical errors is a challenge for naturallanguage processing researchers. As Chinese learners are increasing, developing such a system can help them study Chinese more easily. This paper introduces a bidirectional long short-term memory (BiLSTM) conditional random field (CRF) model to produce the sequences that indicate an error type for every position of...