Asian Language

Research on Asian languages is rapidly expanding, driven by the need to develop robust natural language processing (NLP) tools for the diverse linguistic landscape of the continent. Current efforts focus on addressing the limitations of existing multilingual models, particularly for low-resource languages, through the development of specialized datasets and model architectures like transformer-based LLMs and BiLSTM encoder-decoder models, often incorporating techniques like contrastive learning and instruction tuning. This work is crucial for bridging the digital divide and fostering inclusivity in AI, enabling advancements in various applications such as machine translation, speech recognition, and educational technology across diverse Asian communities.