Design and Implementation of “Russian Audiovisual Speaking” Intelligent System Based on Deep Learning

The purpose of this paper is to design and implement an intelligent teaching system of Russian audio-visual speaking based on deep learning. By analyzing the existing problems in foreign language teaching, this paper discusses how deep learning technology can play a role in Russian audio-visual speaking teaching and improve teaching efficiency and learning effect. Based on RNN-CNN(Recurrent Neural Network-Convolutional Neural Network) model, this system provides an interactive learning platform for Russian learners, aiming to enhance their interest and effect in language learning. Through the detailed description of the system design and implementation process, and the analysis of the system test results, this paper shows the feasibility and effectiveness of the intelligent teaching system. In the experimental stage, four experiments were designed to evaluate the influence of the deep learning-based “Russian Audiovisual speaking” intelligent teaching system on learners in different dimensions. In the first speech recognition accuracy experiment, the RNN-CNN model achieved 92% accuracy after 100 training cycles. In the interactive engagement experiment, the interaction frequency between learners and the system was positively correlated with the learning time. In the third learning satisfaction experiment, learners' overall satisfaction with the teaching system showed generally positive fluctuations. In the final progress experiment, after using the intelligent teaching system, the learners' Russian listening and speaking ability improved to 85 points on average. From the above experimental results, it can be seen that the intelligent teaching system of “Russian audiovisual speaking” based on deep learning has shown remarkable effects in improving learners' Russian listening and speaking ability. However, there is room for improvement in the overall evaluation and interactive experience of the system. Future research could further explore how to optimize system design to enhance interactivity and user experience to further improve teaching effectiveness.