Future Directions in Defence NLP: Investigating Research Gaps for Low-Resource Languages

This paper examines the integration of Natural Language Processing (NLP) technologies within security and defence domains, particularly focusing on the challenges posed by low-resource languages. Recognizing the critical need for sophisticated technological support to process the vast amounts of unstructured linguistic data in multinational operations and peacekeeping missions, we aim to bridge the research gap in military and defence applications for processing such information. Through a literature review, we identify potential advancements in NLP technologies that cater to low-resource settings, thus facilitating improved communication, intelligence sharing, and operational efficiency. Our analysis underscores the pivotal role of NLP in enhancing the operational effectiveness and strategic capabilities of defence and security organizations, especially in linguistically diverse and computationally constrained environments. By systematically examining existing literature, the study not only highlights significant advancements but also reveals critical gaps and opportunities for future research in the application of NLP technologies for defence and security in the context of linguistic diversity and computational limitations.