Abstract—This study introduces an Artificial Intelligence (AI)-based education platform that enables multilingual learning by integrating real-time speech recognition, Speech-to-Text (STT) translation, automated news parsing, and chatbot support functions. By utilizing Whisper-based speech recognition, Google API multilingual translation, Selenium-based news crawling, and an OpenAI chatbot, learners can access translated lecture scripts, stay informed about the latest AI developments in real time, and receive personalized learning support through natural language interaction. The platform is designed to enhance accessibility, eliminate language barriers, and integrate fragmented educational resources into a cohesive system. System evaluation demonstrated high performance, recording a Word Error Rate (WER) of 4% and a Bilingual Evaluation Understudy (BLEU) score of 85, validating the accuracy and reliability of the transcription and translation modules. A System Usability Scale (SUS) evaluation conducted with 30 participants yielded an average score of 79.5, indicating high user satisfaction across diverse age and experience groups. The modular and reproducible system architecture ensures adaptability to different languages and educational environments. This platform contributes to establishing a standard model for global AI-based education systems by supporting scalable and personalized learning. Future research will focus on expanding language support, enhancing context-aware translation accuracy, developing data-driven employment matching capabilities, and implementing effective strategies for broader service deployment. This integrated approach aims to address current limitations in AI education accessibility and foster the development of global digital talent.
 
Keywords—multilingual education, speech recognition, Artificial Intelligence (AI) chatbot, speech to text translation technology, automation crawling and parsing, real-time learning, AI-powered platform


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