Python-based Text Language Identification

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Mrs.R.Valliyammal; Mrs.S.Nusrath Najeeba; Ms.A.Nandhini

Python-based Text Language Identification

Authors: Mrs.R.Valliyammal, Mrs.S.Nusrath Najeeba, Ms.A.Nandhini

Unique Paper ID: 166490
Volume: 11
Issue: 2
PageNo: 1147-1150

Keywords: Character N-grams Content Filtering LangDetect TextBlob.

Abstract:
Language detection plays a crucial role in natural language processing (NLP) applications, enabling tasks such as content filtering, language-specific text analysis, and multilingual content management. This paper presents an exploration of text language detection techniques using Python, focusing on practical implementations and comparative evaluations of popular libraries and methods. We begin with an overview of the importance of language detection in diverse NLP contexts. Subsequently, we delve into the technical aspects, discussing methodologies such as character n-grams, probabilistic language models, and machine learning classifiers. A detailed comparative analysis of prominent Python libraries, including NLTK, TextBlob, and LangDetect, highlights their strengths, weaknesses, and suitability for different use cases. Finally, we offer recommendations for selecting appropriate tools based on specific application needs. This paper serves as a comprehensive guide for researchers and practitioners seeking effective language detection solutions using Python in real-world applications.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 2
PageNo: 1147-1150

Python-based Text Language Identification

Available:https://ijirt.org/article?manuscript=166490

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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