Building a Part of Speech tagger for the Tamil Language

This chapter explores the acquisition of language resources for low-resource languages in digital discourse, focusing on code-mixed content in social media posts and comments. Comprehensive language resources enhance our understanding of language usage patterns in online discussions. The methodology includes data collection, annotation, and automated tools, resulting in a practical framework. Challenges addressed in the chapter include data diversity, annotation complexity, linguistic variability, limited annotated data, and ethical considerations. Solutions proposed range from robust data preprocessing techniques to contextual analysis approaches, ensuring acquired quality and ethical use of resources. The chapter also discusses future directions, paving the way for further research and technology development in natural language processing and sociolinguistics. This chapter equips researchers and practitioners with essential knowledge and tools for advancing linguistic analysis and technological applications in the evolving digital landscape.

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Systematic Review of Morphological and Semantic Analysis in a Low Resource Language

Matan,

Velvizhy

2024

Advances in Computational Intelligence and Robotics

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Natural language processing discusses the applications of computational technique analysis and synthesis of natural languages. Semantic and morphological analysis are the two basic percepts in the natural language processing domain. Semantic analysis is the process of analyzing the lexical, grammatical, and syntactical parts of the words. The study of words known as morphology focuses on the meaning and structure of words. In this chapter, the authors focus on various morphological analyzers developed for Tamil language. Developing a highly accurate and adaptable morphological analyser is a challenging task. Morphological analyser basically identifies the morphemes and parts of speech for tagging. The atomic version of a word that retains the original meaning is called a morpheme. Morphological analyzer type includes phrase level and word level analyzers. Universal networking language (UNL) is a declarative kind used to express the natural language text using a semantic network. The major applications of UNL are information retrieval system, machine translation system, and UNL-based search engine.

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Building a Part of Speech tagger for the Tamil Language

Cited by 3 publications

References 10 publications

Tamil NLP Technologies: Challenges, State of the Art, Trends and Future Scope

Tamil NLP Technologies: Challenges, State of the Art, Trends and Future Scope

Language Resource Acquisition for Low-Resource Languages in Digital Discourses

Systematic Review of Morphological and Semantic Analysis in a Low Resource Language

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