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Dataset of British English speech recordings for psychoacoustics and speech processing research: The clarity speech corpus

Graetzer, Simone; Akeroyd, Michael A.; Barker, Jon; Cox, Trevor J.; Culling, John F.; Naylor, Graham; Porter, Eszter; Viveros-Muñoz, Rhoddy

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Authors

Simone Graetzer

Jon Barker

Trevor J. Cox

John F. Culling

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GRAHAM NAYLOR GRAHAM.NAYLOR@NOTTINGHAM.AC.UK
Professor of Hearing Sciences

Eszter Porter

Rhoddy Viveros-Muñoz



Abstract

This paper presents the Clarity Speech Corpus, a publicly available, forty speaker British English speech dataset. The corpus was created for the purpose of running listening tests to gauge speech intelligibility and quality in the Clarity Project, which has the goal of advancing speech signal processing by hearing aids through a series of challenges. The dataset is suitable for machine learning and other uses in speech and hearing technology, acoustics and psychoacoustics. The data comprises recordings of approximately 10,000 sentences drawn from the British National Corpus (BNC) with suitable length, words and grammatical construction for speech intelligibility testing. The collection process involved the selection of a subset of BNC sentences, the recording of these produced by 40 British English speakers, and the processing of these recordings to create individual sentence recordings with associated transcripts and metadata.

Citation

Graetzer, S., Akeroyd, M. A., Barker, J., Cox, T. J., Culling, J. F., Naylor, G., …Viveros-Muñoz, R. (2022). Dataset of British English speech recordings for psychoacoustics and speech processing research: The clarity speech corpus. Data in Brief, 41, Article 107951. https://doi.org/10.1016/j.dib.2022.107951

Journal Article Type Article
Acceptance Date Feb 8, 2022
Online Publication Date Mar 5, 2022
Publication Date Apr 1, 2022
Deposit Date Apr 25, 2022
Publicly Available Date Mar 29, 2024
Journal Data in Brief
Electronic ISSN 2352-3409
Publisher Elsevier BV
Peer Reviewed Peer Reviewed
Volume 41
Article Number 107951
DOI https://doi.org/10.1016/j.dib.2022.107951
Keywords Multidisciplinary
Public URL https://nottingham-repository.worktribe.com/output/7679397
Publisher URL https://www.sciencedirect.com/science/article/pii/S2352340922001627

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