In order to improve the teaching effect of American science fiction literature, based on artificial intelligence virtual reality technology, this paper constructs an auxiliary teaching system of intelligent American science fiction literature. Moreover, this paper analyzes the time complexity and space complexity of constructing point cloud spatial topological relations and finding the nearest k neighboring points. Simultaneously, this paper uses CUDA to find k nearest neighbors on the GPU, analyzes the point cloud denoising technology, uses the KD-tree to construct the point cloud topology in the DBSCAN-based denoising method, searches for the k nearest neighbors to complete the mark of the core point and the boundary point. In addition, this paper combines artificial intelligence virtual technology and intelligent algorithms to construct the framework of the auxiliary teaching system of American science fiction literature, and analyze its functional modules. Finally, this paper designs experiments to verify the performance of the model. The research results show that the system constructed in this paper can meet the needs of auxiliary teaching of American science fiction literature.
In order to study the application of multimodal NLP instruction combined with speech recognition based on hybrid deep learning in oral English practice, firstly, the basic principle of speech recognition technology is introduced. The concept of hidden Markov model and three key algorithms are explained, and its simulation and implementation in speech recognition application are realized. The architecture and key technologies of the system are introduced. Then, it introduces the specific application of deep learning in NLP. Finally, Chinese teachers with oral English teaching experience participate in the recording. The effective reading time of each person is 65 minutes, and the reading sentences are 3100 sentences. The total number of people is 80 (40 men and 40 women). The sentences cover 1595 spoken English words. Conduct oral English training. The experimental results show that the recognition accuracy decreases by about 2%, but the recognition speed increases by 10 times. In addition, the scoring accuracy is equivalent to that of the platform system. The accuracy of this method in instruction classification is increased, which verifies the feasibility and effectiveness of this method. In the future, attention mechanism will be used to expand this method.
In order to accurately extract the useful information in English, this paper studies English text analysis combined with a genetic algorithm and establishes a text analysis system. In this method, a text tendency analysis algorithm based on a genetic algorithm language model is proposed, and a Doc2vec text feature representation algorithm integrating the LDA model is designed; the parallelization technology of text analysis algorithm is studied, and the parallelization model of the algorithm by using spark big data platform is designed; the process of English text tendency analysis is studied, and a Chinese text analysis system is designed and implemented based on big data platform, including corpus intake, corpus annotation, corpus storage, model training, model verification, and other modules. In order to verify the feasibility of this subject, the accuracy of the Doc2vec text feature representation algorithm of the fused LDA model designed in the prototype system is tested. The experimental results show that the fused text representation model has high recognition degree, and the AUC value of the ROC curve reaches 0.95. At the same time, this paper tests the text analysis-related algorithms involved in the system. The test results show that the parallel algorithm can greatly improve the efficiency of the system.
Testing is a good teaching tool. The online testing system can realize automatic aggregation, scoring, statistics, and analysis of test questions, which saves a lot of time and money for the organizers and participants, and is an effective means to promote the modernization of education in China. The purpose of implementing English intelligence is to allow teachers and students to make better use of their strengths in the English learning process and to improve English teaching based on the results of quantitative analysis of intelligence, which will play a positive role in promoting quality language education in secondary schools, thus truly reducing the burden on teachers and students. The genetic algorithm is an intelligent algorithm based on natural selection and genetic variation in the world of bionic organisms. It has the remarkable advantages of simplicity and generality, robustness, parallel processing, efficiency, and practicality, and has been widely used in automation and other fields with good results. The method can effectively overcome the traditional problems of slow grouping speed, low success rate, and poor grouping quality. The system is scientific, reasonable, and practical and can meet the needs of users to the maximum extent.
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