Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)

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Language Detection using Natural Language Processing

Authors
A. V. Sriharsha1, *, Muthyala Reddy Jahnavi2, Desai Sakethram Kousik2, Vukyam Hemanth2, Matchandrappa Gari Hari2, Penchala Praveen Vasili3
1Professor, Department of CSE (DS), Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College), Tirupati, India
2UG Scholar, Department of Computer Science and Systems Engineering, Sree Vidyankethan Engineering College, Tirupati, India
3Product Manager, Wellsfargo Inc. Charlotte, Charlotte, USA
*Corresponding author. Email: avsreeharsha@gmail.com
Corresponding Author
A. V. Sriharsha
Available Online 30 July 2024.
DOI
10.2991/978-94-6463-471-6_49How to use a DOI?
Keywords
Natural Language Processing (NLP); Multinomial Naive Bayes classifier; Artificial intelligence; Language translation; Performance evaluation; Text classification
Abstract

Natural Language Processing (NLP) is a rapidly advancing field of artificial intelligence that acts as a bridge between human language and machines. Its uses vary from language translation and sentiment analysis to virtual assistants, impacting a wide range of industries. Language detection is a crucial sub-task of NLP that automatically recognizes the language in a given text. The Mul- tinomial Naive Bayes classifier's effectiveness and performance in text classification, along with NLP feature engineering, make it a suitable option for language detection tasks, even when work- ing with multilingual datasets. By integrating NLP techniques and the Multinomial Naive Bayes classifier, the proposed method offers a strong and precise language detection approach. Exper- iments conducted on diverse textual data show promising outcomes, even when dealing with noise and incomplete information. Accurate language identification improves the usability and efficiency of various NLP applications, promoting cross-cultural communication and contrib- uting to a more inclusive and interconnected digital environment.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
Series
Advances in Computer Science Research
Publication Date
30 July 2024
ISBN
978-94-6463-471-6
ISSN
2352-538X
DOI
10.2991/978-94-6463-471-6_49How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - A. V. Sriharsha
AU  - Muthyala Reddy Jahnavi
AU  - Desai Sakethram Kousik
AU  - Vukyam Hemanth
AU  - Matchandrappa Gari Hari
AU  - Penchala Praveen Vasili
PY  - 2024
DA  - 2024/07/30
TI  - Language Detection using Natural Language Processing
BT  - Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
PB  - Atlantis Press
SP  - 507
EP  - 517
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-471-6_49
DO  - 10.2991/978-94-6463-471-6_49
ID  - Sriharsha2024
ER  -