Dataset for the recognition of Kurdish sound dialects
Dialect recognition System (DRS) is a highly significant subject within the field of speech analysis. The performance of speech recognition systems is adversely impacted by factors such as the age, gender, and dialect features of the speaker. In order to address variations in dialect, it is possible...
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| Veröffentlicht in: | Data in brief Jg. 53; S. 110231 |
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01.04.2024
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| Abstract | Dialect recognition System (DRS) is a highly significant subject within the field of speech analysis. The performance of speech recognition systems is adversely impacted by factors such as the age, gender, and dialect features of the speaker. In order to address variations in dialect, it is possible to incorporate DRS into speech recognition systems. The system can be configured to utilize the appropriate speech recognition model based on the identification of the spoken dialect. Currently, there is a lack of available datasets suitable for the development of automatic dialect recognition systems specifically tailored for the Kurdish language. The proposed dataset under consideration is assessed using experimental data that has been gathered by personnel associated with the Computer Science Department at the University of Halabja. As the Kurdish language has three main dialects: Northern Kurdish (Badini variation), Central Kurdish (Sorani variant), and Hawrami, three dialects are included in the dataset. |
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| AbstractList | Dialect recognition System (DRS) is a highly significant subject within the field of speech analysis. The performance of speech recognition systems is adversely impacted by factors such as the age, gender, and dialect features of the speaker. In order to address variations in dialect, it is possible to incorporate DRS into speech recognition systems. The system can be configured to utilize the appropriate speech recognition model based on the identification of the spoken dialect. Currently, there is a lack of available datasets suitable for the development of automatic dialect recognition systems specifically tailored for the Kurdish language. The proposed dataset under consideration is assessed using experimental data that has been gathered by personnel associated with the Computer Science Department at the University of Halabja. As the Kurdish language has three main dialects: Northern Kurdish (Badini variation), Central Kurdish (Sorani variant), and Hawrami, three dialects are included in the dataset. Dialect recognition System (DRS) is a highly significant subject within the field of speech analysis. The performance of speech recognition systems is adversely impacted by factors such as the age, gender, and dialect features of the speaker. In order to address variations in dialect, it is possible to incorporate DRS into speech recognition systems. The system can be configured to utilize the appropriate speech recognition model based on the identification of the spoken dialect. Currently, there is a lack of available datasets suitable for the development of automatic dialect recognition systems specifically tailored for the Kurdish language. The proposed dataset under consideration is assessed using experimental data that has been gathered by personnel associated with the Computer Science Department at the University of Halabja. As the Kurdish language has three main dialects: Northern Kurdish (Badini variation), Central Kurdish (Sorani variant), and Hawrami, three dialects are included in the dataset.Dialect recognition System (DRS) is a highly significant subject within the field of speech analysis. The performance of speech recognition systems is adversely impacted by factors such as the age, gender, and dialect features of the speaker. In order to address variations in dialect, it is possible to incorporate DRS into speech recognition systems. The system can be configured to utilize the appropriate speech recognition model based on the identification of the spoken dialect. Currently, there is a lack of available datasets suitable for the development of automatic dialect recognition systems specifically tailored for the Kurdish language. The proposed dataset under consideration is assessed using experimental data that has been gathered by personnel associated with the Computer Science Department at the University of Halabja. As the Kurdish language has three main dialects: Northern Kurdish (Badini variation), Central Kurdish (Sorani variant), and Hawrami, three dialects are included in the dataset. |
| ArticleNumber | 110231 |
| Author | Ghafoor, Karzan J. Abdulrahman, Ayub O. Rawf, Karwan M. Hama Karim, Sarkhel H. Taher |
| Author_xml | – sequence: 1 givenname: Karwan M. Hama orcidid: 0000-0002-0350-7435 surname: Rawf fullname: Rawf, Karwan M. Hama email: karwan.hamaraouf@uoh.edu.iq – sequence: 2 givenname: Sarkhel H. Taher surname: Karim fullname: Karim, Sarkhel H. Taher – sequence: 3 givenname: Ayub O. orcidid: 0000-0003-3508-1093 surname: Abdulrahman fullname: Abdulrahman, Ayub O. – sequence: 4 givenname: Karzan J. surname: Ghafoor fullname: Ghafoor, Karzan J. |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38435729$$D View this record in MEDLINE/PubMed |
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| Keywords | Hawrami Dialect recognition Badini Sorani Kurdish dialect |
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| References | Hama Rawf, Mohammed, Abdulrahman, Abdalla, Ghafor (bib0009) 2023; 7 Abdul (bib0004) 2019; 7 Badawi, Saeed, Ahmed, Abdalla, Hassan (bib0008) 2023; 48 Ghafoor, Hama Rawf, Abdulrahman, Taher (bib0002) 2021; 9 Işik, Artuner (bib0003) 2018 Eppler, Benedikt (bib0007) 2017; 5 Abdalla, Qadir, Shakor, Saeed, Jabar, Salam, Amin (bib0005) 2023; 47 Rawf, Kareem, Abdulrahman, Ghafoor (bib0001) 2023; V2 Al-Talabani, Abdul, Ameen (bib0006) 2017; 5 Badawi (10.1016/j.dib.2024.110231_bib0008) 2023; 48 Abdul (10.1016/j.dib.2024.110231_bib0004) 2019; 7 Eppler (10.1016/j.dib.2024.110231_bib0007) 2017; 5 Hama Rawf (10.1016/j.dib.2024.110231_bib0009) 2023; 7 Abdalla (10.1016/j.dib.2024.110231_bib0005) 2023; 47 Rawf (10.1016/j.dib.2024.110231_bib0001) 2023; V2 Al-Talabani (10.1016/j.dib.2024.110231_bib0006) 2017; 5 Ghafoor (10.1016/j.dib.2024.110231_bib0002) 2021; 9 Işik (10.1016/j.dib.2024.110231_bib0003) 2018 |
| References_xml | – volume: 5 start-page: 20 year: 2017 end-page: 23 ident: bib0006 article-title: Kurdish dialects and neighbor languages automatic recognition publication-title: ARO- Sci. J. Koya Univ. – volume: 7 start-page: 566 year: 2019 end-page: 572 ident: bib0004 article-title: Kurdish speaker identification based on one dimensional convolutional neural network publication-title: Comput. Methods Differ. Eq. – volume: 5 start-page: 109 year: 2017 end-page: 130 ident: bib0007 article-title: A perceptual dialectological approach to linguistic variation and spatial analysis of Kurdish varieties publication-title: J. Linguist. Geogr. – volume: 7 start-page: 08 year: 2023 end-page: 14 ident: bib0009 article-title: A comparative study using 2D CNN and transfer learning to detect and classify arabic-script-based sign language publication-title: Acta Inform. Malaysia – volume: 47 year: 2023 ident: bib0005 article-title: A vast dataset for Kurdish handwritten digits and isolated characters recognition publication-title: Data Br. – volume: 9 start-page: 10 year: 2021 end-page: 14 ident: bib0002 article-title: Kurdish dialect recognition using 1D CNN publication-title: ARO- Sci. J. Koya Univ. – volume: V2 year: 2023 ident: bib0001 article-title: A dataset for the classification of different Kurdish dialects publication-title: Mendeley Data – start-page: 1 year: 2018 end-page: 4 ident: bib0003 article-title: A dataset for Turkish dialect recognition and classification with deep learning publication-title: 2018 26th Signal Processing and Communications Applications Conference (SIU), Izmir, Turkey – volume: 48 year: 2023 ident: bib0008 article-title: Kurdish News Dataset Headlines (KNDH) through multiclass classification publication-title: Data Br. – volume: 7 start-page: 08 issue: 1 year: 2023 ident: 10.1016/j.dib.2024.110231_bib0009 article-title: A comparative study using 2D CNN and transfer learning to detect and classify arabic-script-based sign language publication-title: Acta Inform. Malaysia doi: 10.26480/aim.01.2023.08.14 – volume: 9 start-page: 10 issue: 2 year: 2021 ident: 10.1016/j.dib.2024.110231_bib0002 article-title: Kurdish dialect recognition using 1D CNN publication-title: ARO- Sci. J. Koya Univ. – volume: V2 year: 2023 ident: 10.1016/j.dib.2024.110231_bib0001 article-title: A dataset for the classification of different Kurdish dialects publication-title: Mendeley Data – volume: 47 year: 2023 ident: 10.1016/j.dib.2024.110231_bib0005 article-title: A vast dataset for Kurdish handwritten digits and isolated characters recognition publication-title: Data Br. – volume: 48 year: 2023 ident: 10.1016/j.dib.2024.110231_bib0008 article-title: Kurdish News Dataset Headlines (KNDH) through multiclass classification publication-title: Data Br. – start-page: 1 year: 2018 ident: 10.1016/j.dib.2024.110231_bib0003 article-title: A dataset for Turkish dialect recognition and classification with deep learning – volume: 7 start-page: 566 issue: 4 year: 2019 ident: 10.1016/j.dib.2024.110231_bib0004 article-title: Kurdish speaker identification based on one dimensional convolutional neural network publication-title: Comput. Methods Differ. Eq. – volume: 5 start-page: 20 issue: 1 year: 2017 ident: 10.1016/j.dib.2024.110231_bib0006 article-title: Kurdish dialects and neighbor languages automatic recognition publication-title: ARO- Sci. J. Koya Univ. – volume: 5 start-page: 109 issue: 2 year: 2017 ident: 10.1016/j.dib.2024.110231_bib0007 article-title: A perceptual dialectological approach to linguistic variation and spatial analysis of Kurdish varieties publication-title: J. Linguist. Geogr. doi: 10.1017/jlg.2017.6 |
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| SubjectTerms | Badini computer science data collection Dialect recognition gender Hawrami human resources Kurdish dialect Sorani speech |
| Title | Dataset for the recognition of Kurdish sound dialects |
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