Speech Recognition Analysis System for an English Vocabulary Learning System based on 5G Sensor Networks

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Weifeng Zhang


This paper presents a novel approach to enhancing English vocabulary learning through real-time speech recognition analysis leveraging 5G sensor networks. The integration of speech recognition technology with advanced network infrastructure offers unprecedented opportunities for interactive and personalized language learning experiences. By utilizing state-of-the-art algorithms and high-speed, low-latency connectivity, learners can receive immediate feedback on their pronunciation, fluency, and comprehension, thereby facilitating rapid skill development. This paper outlines the components and working principle of the proposed system, highlighting its benefits, challenges, and future directions. Through a comprehensive review of existing literature and case studies, they demonstrate the efficacy and potential of this approach in revolutionizing language education. Additionally, they discuss considerations regarding accuracy, privacy, cost, and infrastructure, providing insights for researchers, educators, and policymakers interested in leveraging technology to enhance language learning outcomes. Overall, this paper contributes to the discourse on the intersection of language education, speech recognition, and 5G technology, paving the way for innovative and effective language learning solutions in the digital age.

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