Pronunciation correction and optimization technology of educational robot based on machine learning in English language learning

In this study, a three-layer closed-loop system architecture of perception-diagnosis-feedback is designed, and a comprehensive analysis of learners' pronunciation is realized through multimodal input of speech signals and lip video information. At the core technology level, this paper proposes a multi-modal feature fusion and robustness enhancement method, and realizes the collaborative detection of phoneme-level and prosodic-level errors by combining the multi-task learning model based on BiLSTM. In addition, the study also designed a multi-dimensional weighted scoring mechanism-Pronunciation Quality Index (PQI) to comprehensively evaluate pronunciation quality and generate personalized feedback strategies according to the seriousness of learners' errors. The experimental results show that the system is significantly superior to the traditional methods in phoneme error detection accuracy, and the average F1-score reaches 90.8%. The correlation coefficient between PQI comprehensive score and expert evaluation reaches 0.91, which verifies its effectiveness and practicability in multi-dimensional pronunciation evaluation. In addition, the learning efficiency of the experimental group is significantly higher than that of the control group, and the learning speed is 2.1 times that of the control group, which further proves the key role of real-time correction and robot feedback in pronunciation training. The effect of multimodal feedback strategy in pronunciation error correction is significantly better than that of single modal feedback, and in the robustness test in noise environment, the system shows excellent performance, and the phoneme error rate (PER) only rises to 19.8% under 0dB strong noise, which is far lower than other models. The pronunciation correction and optimization technology of educational robot based on machine learning proposed in this study has significantly improved the accuracy and learning efficiency of pronunciation correction through technological innovation and multimodal interaction design, and provided an efficient and personalized solution for English language learning, which has broad application prospects.