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A Novel Approach for Spoken Language Identification and Performance Comparison Using Machine Learning-Based Classifiers and Neural Network

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Proceedings of the International e-Conference on Intelligent Systems and Signal Processing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1370))

Abstract

Spoken Language Identification (SLI) is the process of capturing a type of language of a speaker. In this research paper, the used database is created in three different languages, Gujarati, Hindi, and English. Language classification is performed using features like MFCC (Mel Frequency Cepstral Coefficients), Pitch, and average energy. Accuracy values of the created database are evaluated and compared using various pattern classifiers, namely, Fine Tree, Linear Discriminant, Gaussian Naïve Bayes, Linear SVM, Fine KNN, and feed-forward neural network in MATLAB 2019. Performance using individual speech features and hybrid features are compared. Training time of all the classifiers is also evaluated to decide the best among all classifiers.

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Authors and Affiliations

  1. V. T. Patel Department of Electronics & Communication Engineering, C. S. Patel Institute of Technology, Charotar University of Science and Technology, Anand, Gujarat, India

    Vishal Tank, Manthan Manavadaria & Krupal Dudhat

Authors
  1. Vishal Tank
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  2. Manthan Manavadaria
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  3. Krupal Dudhat
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Corresponding author

Correspondence to Vishal Tank .

Editor information

Editors and Affiliations

  1. Department of Electronics and Communication, G H Patel College of Engineering and Technology, Vallabh Vidyanagar, Anand, Gujarat, India

    Falgun Thakkar

  2. Department of Electronics and Communication, G H Patel College of Engineering and Technology, Vallabh Vidyanagar, Anand, Gujarat, India

    Geetali Saha

  3. Department of Electrical and Electronics Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh

    Celia Shahnaz

  4. Department of Computer Science and Information Management, Providence University, Taichung, Taiwan

    Yu-Chen Hu

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Tank, V., Manavadaria, M., Dudhat, K. (2022). A Novel Approach for Spoken Language Identification and Performance Comparison Using Machine Learning-Based Classifiers and Neural Network. In: Thakkar, F., Saha, G., Shahnaz, C., Hu, YC. (eds) Proceedings of the International e-Conference on Intelligent Systems and Signal Processing. Advances in Intelligent Systems and Computing, vol 1370. Springer, Singapore. https://doi.org/10.1007/978-981-16-2123-9_42

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