Title: Machine learning for English teaching: a novel evaluation method

Authors: Yang Yang

Addresses: Huanghe Science and Technology University, Zhengzhou, Henan, China

Abstract: This paper proposes a novel oral English scoring system based on machine learning. The system can be deployed on the end side (mobile app) through the internet and can be used to assist teachers in evaluating students' oral English pronunciation, fluency and the tunnel degree. An attention based Long-Short-Term Memory (LSTM) neural network is employed in the paper, which can process and analyse speech signals effectively. Meantime a large amount of training data is collected for network training. We compare the novel oral English evaluation system and the experts' evaluation results. The verification results show that the oral English evaluation system based on machine learning not only can achieve the ability of the English experts, but also has higher accuracy and can identify more oral pronunciation problems.

Keywords: college English teaching; internet; oral English; machine learning; LSTM; attention.

DOI: 10.1504/IJCAT.2023.132101

International Journal of Computer Applications in Technology, 2023 Vol.71 No.3, pp.258 - 264

Received: 19 Apr 2022
Received in revised form: 06 Jun 2022
Accepted: 13 Jun 2022

Published online: 11 Jul 2023 *

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