Research on the construction of English exam for healthcare professionals in health sector.

LiXi Jin
Wenzhou Business College, Wenzhou, China, 325035

DOI:https://doi.org/10.5912/jcb1120

Abstract:

English is an international language, so it is hard for some students to catch up on the progress of modern English. It's not uncommon for students to have difficulties on exam questions because they are unfamiliar with what is being asked. To address this problem, our research team has developed a way to construct an exam bank based on Hadoop cloud computing that allows students to obtain all of the information they need at their fingertips. We discuss our results in detail below. We investigate the modularization of the English pronunciation level assessment system unfolding based on machine learning to increase the accuracy of English pronunciation level evaluation. When the system is used to evaluate the English pronunciation level, the test results reveal that the misjudgment rate of distinct mispronunciations is less than 1%, demonstrating that it has good evaluation accuracy. An assisted learning system based on the AP scoring method and pronunciation resonance peak comparison technology is proposed for the problem of inaccurate pronunciation scoring and lack of effective feedback of speech recognition technology applied to oral learning, and an in-depth study of speech recognition related theories, speech scoring, and pronunciation correction algorithms is discussed. The English pronunciation training system has achieved real-time pronunciation by following the intended pronunciation of English phonetic symbols and words. All core functionalities of the English pronunciation training system, such as pronunciation following, real-time pronunciation assessment, and pronunciation correction of English phonemes, have been realised and perform as planned. After testing, the system obtained great accuracy in pronunciation scoring, with over 90% closeness to experts' score for vowel and word pronunciation; the effectiveness of pronunciation correction exceeds 80%, which can help learners improve their pronunciation to some extent.