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A dataset for voice-based human identity recognition
This paper introduces a new English speech dataset suitable for training and evaluating speaker recognition systems. Samples were obtained from non-native English speakers from the Arab region over the course of two months. The dataset was divided into two sub-datasets. Ten samples were collected fr...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8958529/ https://www.ncbi.nlm.nih.gov/pubmed/35356317 http://dx.doi.org/10.1016/j.dib.2022.108070 |
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author | Alsaify, Baha’ A. Arja, Hadeel S. Abu Maayah, Baskal Y. Al-Taweel, Masa M. |
author_facet | Alsaify, Baha’ A. Arja, Hadeel S. Abu Maayah, Baskal Y. Al-Taweel, Masa M. |
author_sort | Alsaify, Baha’ A. |
collection | PubMed |
description | This paper introduces a new English speech dataset suitable for training and evaluating speaker recognition systems. Samples were obtained from non-native English speakers from the Arab region over the course of two months. The dataset was divided into two sub-datasets. Ten samples were collected from each speaker for each sub-dataset. The first sub-dataset contains samples of speakers repeating the phrase “Machine learning 1, 2, 3, 4, 5, 6, 7, 8, 9, 10”. The second sub-dataset contains samples for the same speakers speaking randomly for five to ten seconds for each sample. The dataset consists of 150 speakers with a total of 3,000 data samples and about six hours of speech. |
format | Online Article Text |
id | pubmed-8958529 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-89585292022-03-29 A dataset for voice-based human identity recognition Alsaify, Baha’ A. Arja, Hadeel S. Abu Maayah, Baskal Y. Al-Taweel, Masa M. Data Brief Data Article This paper introduces a new English speech dataset suitable for training and evaluating speaker recognition systems. Samples were obtained from non-native English speakers from the Arab region over the course of two months. The dataset was divided into two sub-datasets. Ten samples were collected from each speaker for each sub-dataset. The first sub-dataset contains samples of speakers repeating the phrase “Machine learning 1, 2, 3, 4, 5, 6, 7, 8, 9, 10”. The second sub-dataset contains samples for the same speakers speaking randomly for five to ten seconds for each sample. The dataset consists of 150 speakers with a total of 3,000 data samples and about six hours of speech. Elsevier 2022-03-18 /pmc/articles/PMC8958529/ /pubmed/35356317 http://dx.doi.org/10.1016/j.dib.2022.108070 Text en © 2022 The Author(s). Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Alsaify, Baha’ A. Arja, Hadeel S. Abu Maayah, Baskal Y. Al-Taweel, Masa M. A dataset for voice-based human identity recognition |
title | A dataset for voice-based human identity recognition |
title_full | A dataset for voice-based human identity recognition |
title_fullStr | A dataset for voice-based human identity recognition |
title_full_unstemmed | A dataset for voice-based human identity recognition |
title_short | A dataset for voice-based human identity recognition |
title_sort | dataset for voice-based human identity recognition |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8958529/ https://www.ncbi.nlm.nih.gov/pubmed/35356317 http://dx.doi.org/10.1016/j.dib.2022.108070 |
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