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

Audio British English Clarity Hearing Intelligibility Machine learning Recording Sentence Speech

Journal

Data in brief
ISSN: 2352-3409
Titre abrégé: Data Brief
Pays: Netherlands
ID NLM: 101654995

Informations de publication

Date de publication:
Apr 2022
Historique:
received: 24 11 2021
revised: 07 02 2022
accepted: 08 02 2022
entrez: 4 3 2022
pubmed: 5 3 2022
medline: 5 3 2022
Statut: epublish

Résumé

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.

Identifiants

pubmed: 35242933
doi: 10.1016/j.dib.2022.107951
pii: S2352-3409(22)00162-7
pmc: PMC8881678
doi:

Types de publication

Journal Article

Langues

eng

Pagination

107951

Subventions

Organisme : Medical Research Council
ID : MR/S003576/1
Pays : United Kingdom

Informations de copyright

© 2022 The Authors. Published by Elsevier Inc.

Déclaration de conflit d'intérêts

The authors declare that they have no known competing financial interests or personal relationships which have or could be perceived to have influenced the work reported in this article.

Auteurs

Simone Graetzer (S)

Acoustics Research Centre, University of Salford, United Kingdom.

Michael A Akeroyd (MA)

Hearing Sciences, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, United Kingdom.

Jon Barker (J)

Department of Computer Science, University of Sheffield, United Kingdom.

Trevor J Cox (TJ)

Acoustics Research Centre, University of Salford, United Kingdom.

John F Culling (JF)

School of Psychology, Cardiff University, United Kingdom.

Graham Naylor (G)

Hearing Sciences - Scottish Section, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, United Kingdom.

Eszter Porter (E)

Hearing Sciences, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, United Kingdom.

Rhoddy Viveros-Muñoz (R)

School of Psychology, Cardiff University, United Kingdom.

Classifications MeSH