Published Paper Details:

Artificial Intelligence (AI) has significantly transformed second-language acquisition by providing personalized, interactive, and adaptive learning experiences. This research examines AI's role in Hindi as a Second Language (HSL) learning, emphasizing key technologies such as Natural Language Processing (NLP), Machine Learning (ML), and Speech Recognition. AI-driven platforms, including Duolingo, Google Translate, ChatGPT, and Language Curry, enhance pronunciation, grammar comprehension, vocabulary acquisition, and fluency. Despite these advancements, AI-based language learning tools encounter challenges such as contextual inaccuracies, cultural nuances, idiomatic expressions, and regional dialect variations. This study evaluates AI's effectiveness in overcoming these limitations and highlights areas requiring improvement, including the development of more sophisticated NLP models, AI-human hybrid learning approaches, and expanded Hindi-language datasets for ML training. The findings suggest that while AI enhances Hindi language learning, further refinements are needed to address linguistic complexities effectively. The paper concludes with recommendations for future advancements in AI-driven language education, aiming to make Hindi learning more intuitive and effective.