Development of Mobile Application through the Concept of Artificial Intelligence to Enhance Pronunciation Skill in EFL
Abstract
The utilization of artificial intelligence (AI)-powered mobile applications has demonstrated potential in enhancing pronunciation skills for learners of English as a Foreign Language (EFL). In this study, Natural Language Processing (NLP) was employed for English student learning. Jonglish, an Android mobile application utilizing Machine Translation and Grammarly, served as the platform. Given the novelty of the field in Indonesia, the researchers aimed to investigate the integration of NLP into the creation of Jonglish. To address the research objective, which is to elucidate the development of a mobile application named Jonglish through the concept of AI to enhance pronunciation skills in EFL, the researchers utilized the Life Cycle Machine Learning, specifically the Cross Industry Standard Process for Data Mining (CRISP-DM). The results of testing the dataset revealed a 100% success rate in translating the data into Indonesian and English using TextBlob as a translator. Meanwhile, SpellingCheck achieved a 98% accuracy rate for spelling checks. With technological advancements, the collaboration of AI and mobile application will undoubtedly drive further innovation, enhancing convenience, efficiency, and engagement for users around the world. Following the progress report, the subsequent stage is the model testing and deployment phase. In this phase, developers and AI engineers operationalize the concepts and algorithms developed in earlier stages and bring them to life within mobile applications.
Keywords: artificial intelligent, mobile application, pronunciation, EFL
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