Abstract
This article introduces a WeChat mini-program for Smart Oral Evaluation. In this mini-program, we use Tencent Cloud’s Smart Oral Evaluation interface and divide students into different levels, which can accurately return students’ oral English scores and other details in real time. A typical feature of this algorithm is that it supports voice evaluation covering all ages from children to adults, with multiple modes such as words, sentences, paragraphs and free speech, by means of all-round scoring mechanisms including pronunciation accuracy, fluency, and completeness. The similarity of scores by experts is more than 95%, which can be widely used in oral teaching of Chinese and English. The mini-program based on the scoring algorithm of spoken language recognition solves the problem that the current oral English teaching under one instructor’s guidance cannot be adjusted to the needs of every student in one class. After 70 days of experiments, it is proved that the oral English mini-program proposed in this article helps improve the oral English proficiency of each student.
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Acknowledgements
This research has been supported by Shanghai Dianji University Research Foundation: (Grant No. G2-20-7201-003-05-045), Natural Science Foundation of China (Grant No. 62076160), Natural Science Foundation of Shanghai, China (Grant No. 21ZR1424700).
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Xi, K., Nie, Y., Yang, N., Cai, C., Zhang, A. (2022). The WeChat Mini-program for Oral English Evaluation Based on the Smart Listening Algorithm. In: Xu, R., Cai, C., Zhang, LJ. (eds) Cognitive Computing – ICCC 2021. ICCC 2021. Lecture Notes in Computer Science(), vol 12992. Springer, Cham. https://doi.org/10.1007/978-3-030-96419-1_6
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DOI: https://doi.org/10.1007/978-3-030-96419-1_6
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