Research on a collaborative platform for teaching English in universities based on an intelligent voice system - Junwei Niu; Lijuan Jiang (Systems and Soft Computing)
Online teaching platforms have become an essential component of distance education; however, traditional platforms often suffer from background noise interference and insufficient teacher-student interaction, adversely affecting students' learning outcomes. This study aims to develop an online English teaching platform that integrates collaborative learning features and speech enhancement technology to improve instructional quality and student performance. To address these issues, a speech enhancement model based on a multi-head attention mechanism is implemented to improve speech clarity and interactive experience. Experimental results demonstrate that the model, with five stacked layers and trained over 50 iterations, achieves a minimum error of 0.269 and exhibited excellent speech recovery performance under various signal-to-noise ratio conditions. Teaching evaluations further reveal that students using the proposed platform achieve an average improvement of 5.58 points in overall English listening and speaking abilities, with oral scores increasing by 2.33 points compared to the control group. This research provides effective technical support for online English education and offers new insights for optimizing distance education platforms, with broad application potential and theoretical significance.