Human voices communicating trustworthy intent: A demographically diverse speech audio dataset
Abstract The multi-disciplinary field of voice perception and trustworthiness lacks accessible and diverse speech audio datasets representing diverse speaker demographics, including age, ethnicity, and sex. Existing datasets primarily feature white, younger adult speakers, limiting generalisability....
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-05-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-05267-3 |
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| _version_ | 1850105473719599104 |
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| author | Constantina Maltezou-Papastylianou Reinhold Scherer Silke Paulmann |
| author_facet | Constantina Maltezou-Papastylianou Reinhold Scherer Silke Paulmann |
| author_sort | Constantina Maltezou-Papastylianou |
| collection | DOAJ |
| description | Abstract The multi-disciplinary field of voice perception and trustworthiness lacks accessible and diverse speech audio datasets representing diverse speaker demographics, including age, ethnicity, and sex. Existing datasets primarily feature white, younger adult speakers, limiting generalisability. This paper introduces a novel open-access speech audio dataset with 1,152 utterances from 96 untrained speakers, across white, black and south Asian backgrounds, divided into younger (N = 60, ages 18–45) and older (N = 36, ages 60+) adults. Each speaker recorded both, their natural speech patterns (i.e. “neutral” or no intent), and their attempt to convey their trustworthy intent as they perceive it during speech production. Our dataset is described and evaluated through classification methods between neutral and trustworthy speech. Specifically, extracted acoustic and voice quality features were analysed using linear and non-linear classification models, achieving accuracies of around 70%. This dataset aims to close a crucial gap in the existing literature and provide additional research opportunities that can contribute to the generalisability and applicability of future research results in this field. |
| format | Article |
| id | doaj-art-71ec7b56c7dc46b0b3d7e0b64d0aa511 |
| institution | OA Journals |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-71ec7b56c7dc46b0b3d7e0b64d0aa5112025-08-20T02:39:04ZengNature PortfolioScientific Data2052-44632025-05-0112111110.1038/s41597-025-05267-3Human voices communicating trustworthy intent: A demographically diverse speech audio datasetConstantina Maltezou-Papastylianou0Reinhold Scherer1Silke Paulmann2Department of Psychology and Centre for Brain Science, University of EssexBrain-Computer Interfaces and Neural Engineering Laboratory, School of Computer Science and Electronic Engineering, University of EssexDepartment of Psychology and Centre for Brain Science, University of EssexAbstract The multi-disciplinary field of voice perception and trustworthiness lacks accessible and diverse speech audio datasets representing diverse speaker demographics, including age, ethnicity, and sex. Existing datasets primarily feature white, younger adult speakers, limiting generalisability. This paper introduces a novel open-access speech audio dataset with 1,152 utterances from 96 untrained speakers, across white, black and south Asian backgrounds, divided into younger (N = 60, ages 18–45) and older (N = 36, ages 60+) adults. Each speaker recorded both, their natural speech patterns (i.e. “neutral” or no intent), and their attempt to convey their trustworthy intent as they perceive it during speech production. Our dataset is described and evaluated through classification methods between neutral and trustworthy speech. Specifically, extracted acoustic and voice quality features were analysed using linear and non-linear classification models, achieving accuracies of around 70%. This dataset aims to close a crucial gap in the existing literature and provide additional research opportunities that can contribute to the generalisability and applicability of future research results in this field.https://doi.org/10.1038/s41597-025-05267-3 |
| spellingShingle | Constantina Maltezou-Papastylianou Reinhold Scherer Silke Paulmann Human voices communicating trustworthy intent: A demographically diverse speech audio dataset Scientific Data |
| title | Human voices communicating trustworthy intent: A demographically diverse speech audio dataset |
| title_full | Human voices communicating trustworthy intent: A demographically diverse speech audio dataset |
| title_fullStr | Human voices communicating trustworthy intent: A demographically diverse speech audio dataset |
| title_full_unstemmed | Human voices communicating trustworthy intent: A demographically diverse speech audio dataset |
| title_short | Human voices communicating trustworthy intent: A demographically diverse speech audio dataset |
| title_sort | human voices communicating trustworthy intent a demographically diverse speech audio dataset |
| url | https://doi.org/10.1038/s41597-025-05267-3 |
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