Foundations of statistical natural language processing
Foundations of statistical natural language processing
An intelligent tutoring system for deaf learners of written English
Assets '00 Proceedings of the fourth international ACM conference on Assistive technologies
An empirical study of smoothing techniques for language modeling
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
GramCheck: a grammar and style checker
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Parsing for grammar and style checking
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 2
Correcting ESL errors using phrasal SMT techniques
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
GenERRate: generating errors for use in grammatical error detection
EdAppsNLP '09 Proceedings of the Fourth Workshop on Innovative Use of NLP for Building Educational Applications
Automated Grammatical Error Detection for Language Learners
Automated Grammatical Error Detection for Language Learners
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This paper describes a novel approach for automatic creation of Bangla error corpus for training and evaluation of grammar checker systems. The procedure begins with automatic creation of large number of erroneous sentences from a set of grammatically correct sentences. A statistical Confidence Score Filter has been implemented to select proper samples from the generated erroneous sentences such that sentences with less probable word sequences get lower confidence score and vice versa. Rule based Mal-rule filter with HMM based semi-supervised POS tagger has been used to collect the sentences having improper tag sequences. Combination of these two filters ensures the robustness of the proposed approach such that no valid construction is getting selected within the synthetically generated error corpus. Though the present work focuses on the most frequent grammatical errors in Bangla written text, detail taxonomy of grammatical errors in Bangla is also presented here, with an aim to increase the coverage of the error corpus in future. The proposed approach is language independent and could be easily applied for creating similar corpora in other languages.