Patrice Yemmene ^1,4, Prosper Djiaffeua ² and Basile Difouo ^3,4, ¹ University of Wisconsin Milwaukee, Cameroon ² University of Yaoundé I, Cameroon, ³ University of Maroua, Cameroon, ⁴ Laboratoire Technologies Educatives, Cameroun

In this paper, we discuss the necessity for enhancing NLP capabilities for African under-resourced languages, particularly those spoken in Cameroon. We use the Ngiemboon language as a focal point for developing innovative tagging solutions. We lay the groundwork for creating a part-of-speech (POS) tag set for the Ngiemboon language, focusing on a descriptive study of its parts of speech. We establish NLP as an interdisciplinary field that automates language understanding and generation, highlighting various applications such as machine translation and chatbots. We emphasize the role of POS tagging as a fundamental step in NLP. We highlight the linguistic description of the language as a prerequisite for the development of POS. One aspect of linguistic description is the morphosyntactic analysis of the language, which is essential for understanding linguistic structures and enabling more complex language processing tasks. We emphasize the importance of a well-structured tag set, which should be informed by detailed linguistic analysis.

Part of speech, Natural Language Processing (NLP), Under-resourced language