English vocabulary online teaching based on machine learning recognition and target visual detection

Wu, Jie-Rong; Chen, Baodi

doi:10.3233/jifs-179948

Cited by 12 publications

(6 citation statements)

References 3 publications

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“…As a communication tool, vocabulary not only helps Chinese people communicate with each other quickly and effectively to convey information but also becomes an important breakthrough point for transnational communication, and to put it in a larger context, only by learning English vocabulary well can we maximize the reduction of transnational communication barriers [1][2][3]. Vocabulary is a key factor in determining English performance, and the continuous expansion of vocabulary has always been a core requirement in the whole process of English learning [4].…”

Section: Introductionmentioning

confidence: 99%

The Application of Artificial Intelligence Teaching Software in College English Teaching

Wang,

Huang

2023

Applied Mathematics and Nonlinear Sciences

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This paper first proposes English learning software based on personalized recommendations to enhance students’ interest and motivation in learning college English based on artificial intelligence teaching. Secondly, it consists of constructing a learner model, an English learning resource personalized recommendation algorithm to constitute an English learning resource recommendation model, and using a collaborative decomposition algorithm and a regularization algorithm to integrate the potential, multifaceted trust relationship between users with the traditional scoring matrix, a process that emphasizes that trust between users in English teaching varies by different factors and strengths. Then, a personalized recommendation-based university English learning software was designed, and English learning software applications were analyzed by example. The results showed that the adjusted means of pre and post-test scores of the control group, experimental group one, and experimental group two were 77.37, 80.94, and 75.12, respectively, and the statistical score result F=5.33, P<05 indicated that there was a significant difference in the change of English performance of these three groups, which verified that the teaching software had a facilitating effect on the improvement of English teaching quality.

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Section: Introductionmentioning

confidence: 99%

The Application of Artificial Intelligence Teaching Software in College English Teaching

Wang,

Huang

2023

Applied Mathematics and Nonlinear Sciences

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“…The researchers explored the effects of agricultural irrigation on soil moisture, soil erosion, and soil mechanical properties and how these effects promote or reduce landslide occurrence through a comprehensive analysis of the relevant literature. The literature [15] investigated a method for teaching English vocabulary online based on machine learning recognition and visual detection of targets. To design an online English vocabulary teaching system, the researchers used machine learning algorithms to identify and classify English vocabulary and combine them with target visual detection techniques.…”

Section: Introductionmentioning

confidence: 99%

Characteristics of teaching English and American literature based on multimodality under language acquisition theory

Guan

2023

Applied Mathematics and Nonlinear Sciences

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First, This paper constructs a multimodal teaching model based on teaching contents, activities, learning environment and learning means and examines measures to illustrate teaching English and American literature under language acquisition theory. Secondly, it uses Fourier transform and discrete cosine transform to preprocess audio signals, extracts emotional features from MFCC according to the bidirectional long and short-term memory network algorithm of attention, proposes to use representational learning and attention mechanism to focus on the detected emotional regions, and analyzes the multimodalized teaching of English and American literature course and the emotion of teaching speech reading in multimodal English and American literature. The results showed that on the multimodalized English and American literature course, the experimental class had mean scores of 21.81, 8.04, 6.71, and 7.08 on each test, respectively, and the experimental class outperformed the control class on all tests of English and American literature instruction. On the analysis of speech reading aloud emotion evaluation, the model assessment score and teacher assessment error were 2.3, the correlation coefficient was 0.6982, and the overall performance of the model of speech reading aloud emotion analysis of English and American literature was relatively reliable. Students' literary emotional literacy is developed through this study, and a multidimensional interpretation of English and American literature is achieved.

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“…The word content of English Words is designed from the textbook in which it is taught, and reflects the conceptual meaning and schematic meaning of words through word interpretation, usage, and example sentences in both English and Chinese. Through “check-in” and “ranking”, students and teachers can interact with each other and realize interpersonal meaning (Wu and Chen, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

A Study of English Learning Vocabulary Detection Based on Image Semantic Segmentation Fusion Network

Pan¹

2022

Front. Comput. Neurosci.

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College students learn words always under both teachers' and school administrators' control. Based on multi-modal discourse analysis theory, the analysis of English words under the synergy of different modalities, students improve the motivation and effectiveness of word learning, but there are still some problems, such as the lack of visual modal memory of pictures, incomplete word meanings, little interaction between users, and lack of resource expansion function. To this end, this paper proposes a stepped image semantic segmentation network structure based on multi-scale feature fusion and boundary optimization. The network aims at improving the accuracy of the network model, optimizing the spatial pooling pyramid module in Deeplab V3+ network, using a new activation function Funnel ReLU (FReLU) for vision tasks to replace the original non-linear activation function to obtain accuracy compensation, improving the overall image segmentation accuracy through accurate prediction of the boundaries of each class, reducing the intra-class error in the prediction results. The accuracy compensation is obtained by replacing the original linear activation function with FReLU. Experimental results on the Englishhnd dataset demonstrate that the improved network can achieve 96.35% accuracy for English characters with the same network parameters, training data and test data.

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English vocabulary online teaching based on machine learning recognition and target visual detection

Cited by 12 publications

References 3 publications

The Application of Artificial Intelligence Teaching Software in College English Teaching

The Application of Artificial Intelligence Teaching Software in College English Teaching

Characteristics of teaching English and American literature based on multimodality under language acquisition theory

A Study of English Learning Vocabulary Detection Based on Image Semantic Segmentation Fusion Network

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