Interactive virtual reality environments for English language learning: Immersive technologies to enhance language acquisition and communication skills

Interactive virtual reality (VR) atmospheres are progressively being implemented in language learning to their immersive capacity, making language acquisition much more attractive and productive. Combining immersive knowledge with English language knowledge intends to improve acquisition and speaking abilities by presenting dynamic and interactive situations for learners. This investigation suggests a machine learning (ML) technique named Redefined Harries Hawks optimized Intelligent Support Vector Machine (RHH-ISVM), listening to improve English language learning in a VR atmosphere. A data collection comprising student connections with the VR learning surroundings was focused on communication patterns, language difficulty, and learning development. Noise filtering and the Min-Max normalization approach were applied to the dataset to make certain the quality of the data was preserved. Principal Component Analysis (PCA) is being employed to extract meaningful features, such as communication fluency, vocabulary usage, and appropriate consideration, from the data collection. The suggested construction is by collecting user data during communications in VR surroundings. The RHH-ISVM technique researches these features to support an adaptive learning process. VR environments are leveraged to enhance immersive language acquisition and speaking abilities with personalized feedback and tailored content. RHH-ISVM uses an optimized RHH algorithm fused with ISVM to efficiently categorize and assess learner ability. The proposed technique had the greatest performance accuracy (98.56%), VR score (97.69%), training gain (98.49%), and detection scores (89.74%). The suggested approach dispatches promising consequences, with enhanced learner outcomes in language acquisition and English-speaking ability. This approach demonstrates how immersive VR technologies combined with an intelligent ML model can effectively support language learning by providing personalized and engaging experiences.