| Title |
English Automatic Teaching Intelligent Platform Based on Improved Dynamic Time Warping Algorithm |
| DOI |
https://doi.org/10.5573/IEIESPC.2025.14.2.165 |
| Keywords |
Dynamic time warping; K-means; English teaching; Temporal data; Learning path planning |
| Abstract |
Modern educational concepts are student-centered, emphasizing personalized and comprehensive development of students. However, traditional English teaching methods have problems such as single teaching content and insufficient teacher resources. Based on the dynamic time warping, this study introduces clustering algorithm to construct an automatic intelligent platform for English teaching. On the basis of data analysis and clustering, the constructed English automatic teaching intelligent platform is evaluated. Experiments showed that the proposed algorithm could effectively improve the weaknesses of traditional algorithms. There was no crossing between data points. The clustering effect of data points was significant. The accuracy is the highest at 0.91 under different classification point splits. The research system platform had the highest correlation coefficient for speech recognition, ranging from 0.7 to 0.8. Its center frequency was within 1500. The center frequency variance was within 200. When the number of knowledge points was 50, the average teaching time using the proposed teaching system was reduced by nearly 300 minutes. In summary, the English automatic teaching intelligent platform can solve the problems existing in traditional English teaching methods, improving the effectiveness of English teaching. |