<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper first introduces the architecture of the natural language processing system and then analyzes how natural language processing decomposes the probability distribution function by multi-factor form and Bayesian formula to improve the efficiency of function description. Then, NLM is applied to enhance the statistical coefficients of the N-gram model, which solves the problems of data sparsity and dimensionality disaster. By using natural language understanding in English teaching practice and experimenting with the teaching effect, it was found that the overall English achievement of the experimental group increased by 5.4 points, the average Z-score reached more than 3 points, and 96.6% of the students were interested in the teaching method. The new teaching method is demonstrated to have a significant impact on the improvement of English scores.</p>
</abstract>

This paper first introduces the architecture of the natural language processing system and then analyzes how natural language processing decomposes the probability distribution function by multi-factor form and Bayesian formula to improve the efficiency of function description. Then, NLM is applied to enhance the statistical coefficients of the N-gram model, which solves the problems of data sparsity and dimensionality disaster. By using natural language understanding in English teaching practice and experimenting with the teaching effect, it was found that the overall English achievement of the experimental group increased by 5.4 points, the average Z-score reached more than 3 points, and 96.6% of the students were interested in the teaching method. The new teaching method is demonstrated to have a significant impact on the improvement of English scores.

Practices and Challenges of Artificial Intelligence-Assisted Teaching in Vocational Undergraduate Public English Classrooms

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper first introduces the architecture of the natural language processing system and then analyzes how natural language processing decomposes the...

Practices and Challenges of Artificial Intelligence-Assisted Teaching in Vocational Undergraduate Public English Classrooms

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 28. März 2024

Akzeptiert: 17. Juni 2024

DOI: https://doi.org/10.2478/amns-2024-1873

Schlüsselwörter
Artificial intelligence, Natural language processing, Bayesian algorithm, English teaching

© 2024 Yanhua Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Practices and Challenges of Artificial Intelligence-Assisted Teaching in Vocational Undergraduate Public English Classrooms

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 28. März 2024

Akzeptiert: 17. Juni 2024

DOI: https://doi.org/10.2478/amns-2024-1873

SchlüsselwörterArtificial intelligence, Natural language processing, Bayesian algorithm, English teaching

© 2024 Yanhua Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Artificial intelligence, Natural language processing, Bayesian algorithm, English teaching