Challenges in Developing LRs for Non-Scheduled Languages: A Case of Magahi

TL;DR

This paper discusses the challenges of developing language resources for Magahi, a non-scheduled Indo-Aryan language in India, and presents an annotated corpus created from various sources.

Contribution

It introduces the first annotated corpus for Magahi, addressing resource scarcity for non-scheduled languages and providing a foundation for future language technology development.

Findings

Created an annotated POS corpus for Magahi from diverse sources

Highlights the scarcity of language resources for non-scheduled languages

Provides a basis for future NLP research in Magahi

Abstract

Magahi is an Indo-Aryan Language, spoken mainly in the Eastern parts of India. Despite having a significant number of speakers, there has been virtually no language resource (LR) or language technology (LT) developed for the language, mainly because of its status as a non-scheduled language. The present paper describes an attempt to develop an annotated corpus of Magahi. The data is mainly taken from a couple of blogs in Magahi, some collection of stories in Magahi and the recordings of conversation in Magahi and it is annotated at the POS level using BIS tagset.