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

<p>In this paper, we propose an intelligent speech platform combining SincNet and ResNet network with attention mechanism to extract multiresolution features with Sinc convolutional layer and enhance the feature information by combining the channel attention mechanism. The multi-channel features are fed into the ResNet network to get higher-level feature information. Then multi-scale feature fusion is performed by null-space pyramid pooling, which improves the system’s performance. The intelligent voice platform is applied to actual business English teaching. The results show that the significance of the pre-test and posttest of the experimental class is 0.017, which is less than 0.05. The intelligent voice platform is positively contributing to the improvement of performance. Then the questionnaire was utilized to find out the students’ knowledge and ability, satisfaction and acceptance of this mode, 87.8% of the students thought that their business English level was rising, more than 89.69% of the students in the experimental class expressed their support for the course evaluation, and 91.64% of the students preferred this teaching method. Finally, the students were tested on creativity. The scores of the experimental class and the comparison class were 27.42 and 13.79 respectively, and the creativity scores of the practical class were much better than those of the comparison class. Through the teaching practice of intelligent speech platform, the students’ speaking, expression, independent learning, and problem solving abilities have been greatly improved.</p>
</abstract>

In this paper, we propose an intelligent speech platform combining SincNet and ResNet network with attention mechanism to extract multiresolution features with Sinc convolutional layer and enhance the feature information by combining the channel attention mechanism. The multi-channel features are fed into the ResNet network to get higher-level feature information. Then multi-scale feature fusion is performed by null-space pyramid pooling, which improves the system’s performance. The intelligent voice platform is applied to actual business English teaching. The results show that the significance of the pre-test and posttest of the experimental class is 0.017, which is less than 0.05. The intelligent voice platform is positively contributing to the improvement of performance. Then the questionnaire was utilized to find out the students’ knowledge and ability, satisfaction and acceptance of this mode, 87.8% of the students thought that their business English level was rising, more than 89.69% of the students in the experimental class expressed their support for the course evaluation, and 91.64% of the students preferred this teaching method. Finally, the students were tested on creativity. The scores of the experimental class and the comparison class were 27.42 and 13.79 respectively, and the creativity scores of the practical class were much better than those of the comparison class. Through the teaching practice of intelligent speech platform, the students’ speaking, expression, independent learning, and problem solving abilities have been greatly improved.

Emerging Technologies in Diversified Business English Teaching: A Language Learning Revolution Aided by Artificial Intelligence

Applied Mathematics and Nonlinear Sciences

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

In this paper, we propose an intelligent speech platform combining SincNet and ResNet network with attention mechanism to extract multiresolution features with...

Emerging Technologies in Diversified Business English Teaching: A Language Learning Revolution Aided by Artificial Intelligence

Online veröffentlicht: 26. Feb. 2024

Seitenbereich: -

Eingereicht: 15. Jan. 2024

Akzeptiert: 22. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0594

Schlüsselwörter
Sinc convolutional layer, Attention mechanism, ResNet network, Intelligent speech platform

© 2024 Shufen Chen, published by Sciendo

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

Emerging Technologies in Diversified Business English Teaching: A Language Learning Revolution Aided by Artificial Intelligence

Online veröffentlicht: 26. Feb. 2024

Seitenbereich: -

Eingereicht: 15. Jan. 2024

Akzeptiert: 22. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0594

SchlüsselwörterSinc convolutional layer, Attention mechanism, ResNet network, Intelligent speech platform

© 2024 Shufen Chen, published by Sciendo

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

Schlüsselwörter
Sinc convolutional layer, Attention mechanism, ResNet network, Intelligent speech platform