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:
Data Article
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
Descripción
Sumario: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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