Research on Speech Recognition and Feedback Technology in AI-Driven English Speaking Practice Platforms

In China’s educational environment, the evaluation of English-speaking teaching has always been a challenging task. Compared to written English, the assessment of spoken English not only requires examining students’ grammar and vocabulary usage, but more importantly, assessing their pronunciation, intonation, and fluency. However, traditional English oral pronunciation correction systems often suffer from feedback lag and insufficient accuracy. To overcome these challenges, we have designed an AI driven English speaking evaluation system based on speech recognition (ASR) and feedback technology. This system combines advanced ASR algorithms and AI technology, which can analyze students’ pronunciation in real-time and provide real-time and accurate feedback. The experimental results indicate that the system proposed in this paper has significant advantages. Firstly, it can provide real-time feedback to help students immediately understand their pronunciation issues and make timely adjustments and improvements. Secondly, the feedback accuracy of the system is high, which can identify subtle differences in pronunciation and provide targeted suggestions. Finally, the system also has a good user experience, which can stimulate students’ interest and motivation in learning, and improve the efficiency of English oral learning.