Design of English Spoken Speech Correction System Based on Deep Neural Networks

In the age of artificial intelligence, enhancing the spoken English proficiency of English learners in China is of great significance and holds significant research value. On one hand, language transfer plays a pivotal role throughout the process of second language learning, particularly during its initial stages. On the other hand, negative transfer from one's native language and cultural-specific thinking patterns often poses a barrier to effective foreign language acquisition. Initially, a brief overview of second language learning will be provided, with an explanation of the implications of language transfer. The main content will then delve into a thorough analysis of the negative transfer of Chinese in spoken English learning. This analysis will delve into the differences between Chinese and English in terms of sound, vocabulary, and cultural elements. Therefore, I aim to present some effective methods for improving English language teaching and learning. These strategies will address theoretical and methodological implications, syllabus design, and assessment practices. The objective is to minimize or eliminate the impact of negative transfer in English learning as well as teaching.