Text-based Language Identifier using Multinomial Naïve Bayes Algorithm


Sunita Rawat
Lakshita Werulkar
Sagarika Jaywant


Language Identification is among the crucial steps in any NLP based application. Text - based documents and webpages are rapidly increasing in the modern Internet. It is simple to locate documents written in different languages from all across the world that are available with just one click. Therefore, a language identifier is absolutely necessary in order to help the user interpret the content. Language identification has so far tended to be more concentrated on European languages and is still rather limited for Indian Traditional Languages. Many researchers have become more interested in the study of language identification for similar languages from popular languages. In this paper, Multinomial Na¨ıve Bayes Algorithm is used for detecting languages in Devanagari like Marathi, Sanskrit and Hindi, and three European languages French, Italian and English. An experiment done on
datasets of each language has produced satisfactorily accurate results after training and testing the model.


How to Cite
Rawat, S., Werulkar, L., & Jaywant, S. (2023). Text-based Language Identifier using Multinomial Naïve Bayes Algorithm. International Journal of Next-Generation Computing, 14(1). https://doi.org/10.47164/ijngc.v14i1.1024


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