CLNov 30, 2021

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

arXiv:2111.15322v13 citations
Originality Synthesis-oriented
AI Analysis

This addresses the problem of resource scarcity for Magahi speakers and researchers, but it is incremental as it applies existing methods to a new language.

The paper tackles the lack of language resources for Magahi, a non-scheduled Indo-Aryan language, by developing an annotated corpus using data from blogs, stories, and conversations, with POS tagging based on the BIS tagset.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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