Named Entity Recognition of Kumauni Language using Machine Learning (ML)

Abstract

Communication between humans is impossible without the use of language. Natural Language Processing (NLP) is a technique that is used so that computers can comprehend various natural languages. Named Entity Recognition (NER) is a subtask of information extraction that aims to discover and categorize the components in given text into pre-defined categories. NER is an abbreviation for the phrase “named entity recognition”. Machine translation, question-answering systems, and automatic summarization are examples of the types of NLP tasks that can benefit from NER. The purpose of this research is to investigate whether or if it is possible to create a chatbot that converses in the Kumaon language, as well as any potential difficulties that could arise in the process. In addition to this, the authors provide an in-depth examination of Kumaoni as well as a mapping of the language into other languages to make its use in industrial processing more accessible. In this study author utilize a previously researched based on the named entity recognition of languages from the databases such as Scopus, web of science, IEEE, Google Scholar, Cite SeerX, Cross Ref etc. in their study. The research activity possesses the capacity to fundamentally transform the field of linguistic evaluation in the Kumaon region by employing sophisticated machine learning (ML) techniques to explore the complex domain of NER (named entity recognition) for the Kumauni language.