Abstract With the development of artificial intelligence technology, computer-aided pronunciation training systems are gradually receiving attention. However, existing systems have some issues, such as inaccurate judgments and untimely feedback. We propose an improved solution based on deep learning and reinforcement learning to address these issues. This scheme first uses deep learning algorithms to model English pronunciation. Specifically, we used models such... With the development of artificial intelligence technology, computer-aided pronunciation training systems are gradually receiving attention. However, existing systems have some issues, such as inaccurate judgments and untimely feedback. We propose an improved solution based on deep learning and reinforcement learning to address these issues. This scheme first uses deep learning algorithms to model English pronunciation. Specifically, we used models such as Convolutional Neural Networks (CNN) and Long Short Term Memory Networks (LSTM) to extract and classify features of pronunciation audio. At the same time, we also used reinforcement learning algorithms to automatically adjust training difficulty and feedback methods based on students’ pronunciation to provide more personalized and accurate training effects. Through experimental verification, we found that the improved scheme based on deep learning and reinforcement learning can significantly improve the accuracy and real-time performance of the CAPT system in English pronunciation judgment. This scheme has higher learning efficiency and lower learning costs than traditional pronunciation training systems. In addition, students also showed higher satisfaction and stronger learning motivation towards the program. Read More Read Less

Abstract With the improvement of China’s international status, the demand for foreign language application talents is becoming increasingly significant for hosting the Winter Olympics. To meet this demand, we propose a solution based on the Viterbi algorithm aimed at cultivating applied talents with foreign language skills and professional knowledge required for the Winter Olympics. This plan first determines the foreign language... With the improvement of China’s international status, the demand for foreign language application talents is becoming increasingly significant for hosting the Winter Olympics. To meet this demand, we propose a solution based on the Viterbi algorithm aimed at cultivating applied talents with foreign language skills and professional knowledge required for the Winter Olympics. This plan first determines the foreign language skills and professional knowledge required for the Winter Olympics, including English, French, German and other languages, and professional knowledge related to ice and snow sports. Then, we used the Viterbi algorithm to identify students’ learning patterns and difficulties based on their learning trajectories and performance data, providing them with more personalized and targeted teaching solutions. In addition, we have combined the cultivation of professional knowledge and foreign language skills in ice and snow sports to enhance students’ practical abilities and comprehensive qualities. Through experimental verification, we found that the Viterbi algorithm-based solution can significantly improve students’ foreign language application ability and professional knowledge level. This program has higher teaching efficiency and lower teaching costs than traditional training models. In addition, students also showed higher satisfaction and stronger learning motivation towards the program. Read More Read Less

Abstract With the continuous development of Internet technology, the application of search algorithms in the tourism economy is becoming increasingly widespread. This article aims to explore the development strategies of the tourism economy under search algorithms and research on market resource integration. Firstly, this article analyzes the importance of search algorithms in developing the tourism economy, including improving the visibility of... With the continuous development of Internet technology, the application of search algorithms in the tourism economy is becoming increasingly widespread. This article aims to explore the development strategies of the tourism economy under search algorithms and research on market resource integration. Firstly, this article analyzes the importance of search algorithms in developing the tourism economy, including improving the visibility of tourism destinations, promoting the upgrading of the tourism industry, and optimizing the supply structure of tourism products. Then, from the perspective of market resource integration, this article explores how search algorithms integrate tourism market resources, including resource integration in tourist attractions, hotels, catering, transportation, and other aspects. Finally, this article proposes strategies for developing the tourism economy based on search algorithms, including optimizing search algorithms, strengthening supervision of the tourism market, promoting the upgrading of the tourism industry, and strengthening innovation of tourism products. Read More Read Less