Design of English Speaking Exam System Based on Particle Swarm Optimization Algorithm

The English oral exam is an important component of language learning, but the traditional exam mode uses face-to-face exams between teachers and students. This oral exam mode has strong subjectivity for examiners, and their oral proficiency, pronunciation, and other factors directly affect the performance of candidates. Although there are videos of the entire exam sent to the exam center, the exam center can only conduct sampling inspections at most, resulting in unfair grading. In this regard, this article designs an English speaking exam system based on PSO (Particle Swarm Optimization), which can achieve online registration and login authentication for candidates. Online exams use computers to extract test questions from the established question bank according to the paper formation algorithm, and form test papers that meet the requirements. It is an effective means to achieve standardized and scientific examination. Implement online testing of different types of English knowledge, allowing users to analyze and count their test scores. And through experimental testing, the experimental results show that PSO has reached a convergence value of 682 when the number of iterations is 1150, while the GA (Genetic Algorithm) algorithm needs 2100 iterations to reach the optimal value. It can be seen that the algorithm proposed in this article is more suitable for English oral testing.