Linguistic Resource

Linguistic resources, encompassing corpora, lexicons, and annotated datasets, are crucial for advancing natural language processing (NLP) across diverse languages. Current research emphasizes addressing the scarcity of resources for low-resource languages, focusing on data collection methods, cross-lingual transfer learning techniques, and the development of multilingual models, often employing architectures like GRUs and leveraging sentence embeddings. These efforts are vital for broadening NLP's reach, enabling applications like machine translation, named entity recognition, and readability assessment in a wider range of languages and dialects, ultimately fostering inclusivity and accessibility in technological advancements.