Zhejiang University of Science & Technology, Hangzhou, Zhejiang 310023, China.
Comput Intell Neurosci. 2022 Jun 10;2022:7361746. doi: 10.1155/2022/7361746. eCollection 2022.
Generally, in-depth learning has been extensively employed in numerous industries to enhance the growth of economic globalization since the dawn of the big data age. At the same time, the demand for foreign language talent has risen dramatically, and more and more businesses are steadily raising their English proficiency standards. International interactions, as well as scientific and technical exchanges, are influenced by English communicating competence. As a result, colleges and universities place a high value on students studying English. However, English learning is also a compulsory course in Colleges and universities, which is different from other courses. Therefore, in setting teaching objectives, arranging teaching activities, and compiling teaching contents, we should highlight students' personalized needs and formulate learning plans in combination with the individual requirements of each student. Aiming at this problem, this paper adopts the deep learning method to study the personalized learning of College English. Deep learning algorithm utilization in the development of college students' English learning reduces teachers' workload and focuses more on students' personalized needs, which is beneficial to teachers' teaching and students' learning. By analyzing the deep learning neural network model, the process of English speech recognition is described, and the characteristic parameters of English speech are extracted. Then compare and explain the characteristics of deep learning and shallow learning, analyze the relationship between them, and clarify the route of deep learning. Finally, the effect of College Students' personalized learning is analyzed by random sampling, and the effect of College English personalized learning based on deep learning is explained from two aspects: listening effect and reading practice.
一般来说，自大数据时代以来，深度学习已经广泛应用于许多行业，以促进经济全球化的发展。与此同时，对外语人才的需求急剧增加，越来越多的企业稳步提高英语水平标准。国际交流以及科技交流都受到英语交际能力的影响。因此，高校重视学生学习英语。然而，英语学习也是高校的必修课，与其他课程不同。因此，在制定教学目标、安排教学活动和编写教学内容时，我们应该突出学生的个性化需求，并结合每个学生的个体要求制定学习计划。针对这个问题，本文采用深度学习方法研究大学英语的个性化学习。深度学习算法在大学生英语学习中的应用减少了教师的工作量，并更加关注学生的个性化需求，这有利于教师教学和学生学习。通过分析深度学习神经网络模型，描述了英语语音识别的过程，并提取了英语语音的特征参数。然后比较和解释了深度学习和浅层学习的特点，分析了它们之间的关系，阐明了深度学习的路径。最后，通过随机抽样分析了大学生个性化学习的效果，并从听力效果和阅读实践两个方面解释了基于深度学习的大学英语个性化学习的效果。
