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Hybrid AI for Hakka Language Translation by change6108 is a document available to read on EtoBox.

This study introduces a hybrid AI-driven translation system that combines phrase-based machine translation (PBMT) and neural machine translation (NMT) to improve translation quality for low-resource languages, specifically the Hakka language. The system employs a recursive learning framework to enhance translation accuracy by dynamically generating parallel corpora and refining translations. The findings indicate that this hybrid approach effectively addresses data scarcity challenges and supports cultural

Author

change6108

Language

EN