The OPL optimization programming language
The OPL optimization programming language
Predictive Statistical Models for User Modeling
User Modeling and User-Adapted Interaction
Logic programming in the context of multiparadigm programming: the Oz experience
Theory and Practice of Logic Programming
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Machine Learning
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Constraint Logic Programming using Eclipse
Constraint Logic Programming using Eclipse
Speech and Language Processing (2nd Edition)
Speech and Language Processing (2nd Edition)
Automatic learning of dialogue strategy using dialogue simulation and reinforcement learning
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Treebanks gone bad: Parser evaluation and retraining using a treebank of ungrammatical sentences
International Journal on Document Analysis and Recognition
The Design of the Zinc Modelling Language
Constraints
CSIEC: A computer assisted English learning chatbot based on textual knowledge and reasoning
Knowledge-Based Systems
Sound and efficient inference with probabilistic and deterministic dependencies
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
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
Designing a feedback component of an intelligent tutoring system for foreign language
Knowledge-Based Systems
Comparing user simulation models for dialog strategy learning
NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
MiniZinc: towards a standard CP modelling language
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
An ontology-based universal design knowledge support system
Knowledge-Based Systems
A probabilistic approach to fraud detection in telecommunications
Knowledge-Based Systems
POMY: a conversational virtual environment for language learning in POSTECH
SIGDIAL '11 Proceedings of the SIGDIAL 2011 Conference
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This paper presents an automated method to generate realistic grammatical errors that can perform crucial functions for advanced technologies in computer-assisted language learning (CALL), including generating corrective feedback in dialog-based CALL (DB-CALL) systems, simulating a language learner to optimize tutoring strategies, and generating context-dependent grammar quizzes as educational materials. The goal of this study is to make grammatical errors generated by automatic simulators more realistic. To generate realistic errors, expert knowledge of language learners' error characteristics was imported into a statistical modeling system that uses Markov logic, which provides a theoretically sound way to encode knowledge into probabilistic first-order logic. We learned the weights of first-order formulas from a learner corpus. The improved quality of the proposed method was demonstrated through comparative experiments using automatic evaluations (precision and recall rate and Kullback-Leibler divergence between error distributions) and human assessments. The proposed method increased precision by 6% and recall by 8.33% averaged across all proficiency levels. It also exhibited a relative improvement of 37.5% in the average Kullback-Leibler divergence. Judgment by human evaluators showed that the proposed method increased the average scores in two different evaluation tasks by 7 and by 0.411. Finally, we present a measure of labor savings to help predict the time and cost associated with this method for those who plan to exploit grammatical error simulation for their applications. The results indicate that using the proposed method could reduce the grammatical error generation time by 59% in average.