| Title |
Applying AR Technology Integrating Unity3D with the Vuforia SDK for Oral English Teaching |
| Authors |
(Wei Huang) ; (Haiyan Zhang) |
| DOI |
https://doi.org/10.5573/IEIESPC.2023.12.6.457 |
| Keywords |
U-nity3D; Vuforia SDK; AR; CNN; Oral English teaching |
| Abstract |
With the rapid progress of information technology, its application to teaching has gradually become a hot topic in the education field. Augmented reality (AR) combines virtual and real characteristics that can improve comprehension in a virtual environment, bringing new development opportunities to oral English teaching. Based on integration of the Vuforia SDK in the U-nity3D augmented reality engine, this research applies AR technology to spoken English teaching, improves a convolutional neural network (CNN), and proposes an English speech recognition system based on a connectionist temporal classification (CTC)-CNN (maxout). The results from experiments varying the number of iterations and the loss value, the proposed model converges after 80 iterations with strong performance. In recognition of spoken English with or without noise, the accuracy of this method was highest at 0.957 and 0.894, respectively, which is better than the CTC-CNN (sigmoid) model. In recognizing six kinds of spoken English, the accuracy of the CTC-CNN (maxout) model stabilizes at about 95%, with the highest accuracy at 97%. The accuracy rate shows that the method can be effectively applied to oral English teaching, and can provide a new reference method for innovations in oral English teaching and the improvement of teaching efficiency. |