Kurdish Dialect Recognition using 1D CNN

ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY

View Publication Info
 
 
Field Value
 
Title Kurdish Dialect Recognition using 1D CNN
 
Creator Ghafoor, Karzan J.
Hama Rawf, Karwan M.
Abdulrahman, Ayub O.
Taher, Sarkhel H.
 
Subject Convolution neural network
Deep learning
Dialect recognition
Machine learning
 
Description Dialect recognition is one of the most attentive topics in the speech analysis area. Machine learning algorithms have been widely used to identify dialects. In this paper, a model that based on three different 1D Convolutional Neural Network (CNN) structures is developed for Kurdish dialect recognition. This model is evaluated, and CNN structures are compared to each other. The result shows that the proposed model has outperformed the state of the art. The model is evaluated on the experimental data that have been collected by the staff of department of computer science at the University of Halabja. Three dialects are involved in the dataset as the Kurdish language consists of three major dialects, namely Northern Kurdish (Badini variant), Central Kurdish (Sorani variant), and Hawrami. The advantage of the CNN model is not required to concern handcraft as the CNN model is featureless. According to the results, the 1 D CNN method can make predictions with an average accuracy of 95.53% on the Kurdish dialect classification. In this study, a new method is proposed to interpret the closeness of the Kurdish dialects by using a confusion matrix and a non-metric multi-dimensional visualization technique. The outcome demonstrates that it is straightforward to cluster given Kurdish dialects and linearly isolated from the neighboring dialects.
 
Publisher Koya University
 
Date 2021-10-15
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed article
Text
 
Format application/pdf
 
Identifier http://aro.koyauniversity.org/index.php/aro/article/view/837
10.14500/aro.10837
 
Source ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY; Vol. 9 No. 2 (2021): Issue Seventeen; 10-14
2307-549X
2410-9355
 
Language eng
 
Relation http://aro.koyauniversity.org/index.php/aro/article/view/837/221
 
Rights Copyright (c) 2021 Karzan J. Ghafoor, Karwan M. Hama Rawf, Ayub O. Abdulrahman, Sarkhel H. Taher
https://creativecommons.org/licenses/by-nc-sa/4.0
 

Contact Us

The PKP Index is an initiative of the Public Knowledge Project.

For PKP Publishing Services please use the PKP|PS contact form.

For support with PKP software we encourage users to consult our wiki for documentation and search our support forums.

For any other correspondence feel free to contact us using the PKP contact form.

Find Us

Twitter

Copyright © 2015-2018 Simon Fraser University Library