Named Entity Recognition for Konkani Speech

Abstract

Named Entity Recognition (NER) is the procedure of recognizing and classifying all the proper nouns into pre-defined classes such as locations, persons, organization, date and others. NER has many uses such as Speed up the hiring process by summarizing applicants' CVs, improve internal workflows by categorizing employee complaints and questions, Enable students and researchers to find relevant material faster by summarizing papers and archive material and highlighting key terms, topics, and themes and has many other uses. To work on NER in Indian languages is a difficult and challenging task and also limited due to scarcity of resources, but it has started to appear recently. A named entity recognizer (NER), an essential tool for natural language processing (NLP), is presented for the first time for the Konkani speech as per my knowledge. In this paper NER for Konkani Speech is proposed. The Proposed model is able to identify named entities from Konkani audios and classify them into pre-defined categories like person, location, date and organization.