Innovative Language Translation With Artificial Intelligence

The rapid evolution of AI in language processing has improved machine translation, yet challenges remain in translating slang due to cultural and contextual nuances. This study presents an AI-driven model for translating Telugu slang into English and Hindi, integrating neural machine translation (NMT) with transformer-based deep learning. A custom dataset of Telugu slang from social media, literature, and conversations enhances contextual accuracy. Using context-aware embeddings and attention mechanisms, the model achieves superior fluency and relevance. Performance evaluation confirms its effectiveness over traditional methods. An adaptive learning system ensures continuous refinement. Future work will expand the dataset, improve disambiguation, and integrate real-time speech-to-text translation