Dr Simone Graetzer S.N.Graetzer@salford.ac.uk
Research Fellow
Dr Simone Graetzer S.N.Graetzer@salford.ac.uk
Research Fellow
MA Akeroyd
J Barker
Prof Trevor Cox T.J.Cox@salford.ac.uk
Professor
JF Culling
G Naylor
E Porter
RV Muñoz
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.
Journal Article Type | Article |
---|---|
Acceptance Date | Feb 8, 2022 |
Online Publication Date | Feb 15, 2022 |
Publication Date | Apr 1, 2022 |
Deposit Date | Feb 17, 2022 |
Publicly Available Date | Feb 17, 2022 |
Journal | Data in Brief |
Print ISSN | 2352-3409 |
Electronic ISSN | 2352-3409 |
Publisher | Elsevier |
Volume | 41 |
Pages | 107951 |
DOI | https://doi.org/10.1016/j.dib.2022.107951 |
Publisher URL | https://doi.org/10.1016/j.dib.2022.107951 |
Related Public URLs | https://www.journals.elsevier.com/data-in-brief/ |
Additional Information | Funders : Engineering and Physical Sciences Research Council (EPSRC) Projects : Challenges to Revolutionise Hearing Grant Number: EP/S031448/1, EP/S031308/1, EP/S031324/1 and EP/S030298/1 |
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Licence
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Continuous evaluative and pupil dilation response to soundscapes
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Presentation / Conference
Machine learning challenges to revolutionise hearing device processing
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Presentation / Conference
Clarity-2021 challenges : machine learning challenges for advancing hearing aid processing
(2021)
Presentation / Conference Contribution
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