A Comparative Study for Language Recognition using Learning-based Approaches

Citation

Meng, Chew Chee and Lim, Kian Ming and Lee, Chin Poo and Chan, Xian Yang and Lew, Ching Hong and Song, Veron Wei Ru (2023) A Comparative Study for Language Recognition using Learning-based Approaches. In: 2023 11th International Conference on Information and Communication Technology (ICoICT), 23-24 August 2023, Melaka, Malaysia.

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Abstract

Language recognition is helpful for determining the natural language in a given document or part of text. Language recognition has attracted more attention in recent times due to its wide-ranging applications, including speech translation, multilingual speech recognition and more. Indeed, language recognition should be effective to ensure practical implementation. Therefore, learning-based approaches are introduced to enhance the effectiveness of language recognition. In this paper, a total of six learning-based approaches have been implemented for solving the language recognition problem. Experiments and evaluations are conducted to study the effectiveness of these learning-based approaches on identifying 5 different languages which are English, German, Czech, French, and Swedish. The experimental results show that the 1D-CNN model achieves the highest accuracy score of 65.99%.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Language Recognition, Machine Learning, Deep Learning, Convolutional Neural Network
Subjects: Q Science > Q Science (General) > Q300-390 Cybernetics
Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 31 Oct 2023 01:05
Last Modified: 31 Oct 2023 01:05
URII: http://shdl.mmu.edu.my/id/eprint/11759

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