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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...

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Detalles Bibliográficos
Autores principales: Alsaify, Baha’ A., Arja, Hadeel S. Abu, Maayah, Baskal Y., Al-Taweel, Masa M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
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.
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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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