深度回声状态网络模型在英语写作辅助和语法纠错中的性能评估与改进n

Dongyun Chen
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引用次数: 0

摘要

引言:英语写作辅导与语法纠错绩效评价模型的研究是非常必要的,这不仅有利于教师写作辅导资源的合理配置,更有利于及时有效地纠正学生的语法错误.目的:英语写作辅导与语法纠错绩效评价模型的研究是非常必要的,这不仅有利于教师写作辅导资源的合理配置,更有利于及时有效地纠正学生的语法错误:针对目前英语写作语法纠错绩效评价方法中存在的量化不具体、精度不高、实时性不强等问题。方法:本文提出了一种基于深度回波态网络的语法纠错绩效评价方法与淘金优化算法。首先,通过分析英语写作辅助和语法纠错的过程,提取语法纠错类型的评价特征,构建性能评价体系;然后,通过gold rush优化算法改进深度置信网络,构建语法纠错性能评价模型;最后,通过仿真实验进行分析。结果:结果表明,本文提出的方法提高了评价的准确性、鲁棒性。结论:解决了英语写作语法纠错性能评估方法应用中存在的量化不具体、精度不高、实时性不强等问题。
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Performance Evaluation and Improvement of Deep Echo State Network Models in English Writing Assistance and Grammar Error Correctionn
INTRODUCTION: The research on the performance evaluation model of English writing tutoring and grammar error correction is very necessary, which is not only conducive to the rational allocation of teachers' writing tutoring resources, but also more conducive to the timely and effective correction of students' grammatical errors.OBJCTIVES: Aiming at the problems of non-specific quantification, low precision, and low real-time performance evaluation methods for English writing grammar error correction in current methods.METHODS: This paper proposes a grammar error correction performance evaluation method based on deep echo state network with gold rush optimisation algorithm. Firstly, by analysing the process of English writing assistance and grammatical error correction, we extract the evaluation features of grammatical error correction type and construct the performance evaluation system; then, we improve the deep confidence network through the gold rush optimization algorithm and construct the grammatical error correction performance evaluation model; finally, we analyse it through simulation experiments.RESULTS: The results show that the proposed method improves the evaluation accuracy, robustness. The absolute value of the relative error of the evaluation value of the syntactic error correction performance of the method is controlled within the range of 0.02.CONCLUSION: The problems of non-specific quantification, low precision and low real-time performance of the application of English writing grammar error correction performance assessment methods are solved.
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