Paper: Realistic Grammar Error Simulation using Markov Logic

ACL ID P09-2021
Title Realistic Grammar Error Simulation using Markov Logic
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2009

The development of Dialog-Based Computer- Assisted Language Learning (DB-CALL) sys- tems requires research on the simulation of language learners. This paper presents a new method for generation of grammar errors, an important part of the language learner simula- tor. Realistic errors are generated via Markov Logic, which provides an effective way to merge a statistical approach with expert know- ledge about the grammar error characteristics of language learners. Results suggest that the distribution of simulated grammar errors gen- erated by the proposed model is similar to that of real learners. Human judges also gave con- sistently close judgments on the quality of the real and simulated grammar errors.