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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.
Affiliation
  • Graetzer S; Acoustics Research Centre, University of Salford, United Kingdom.
  • Akeroyd MA; Hearing Sciences, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, United Kingdom.
  • Barker J; Department of Computer Science, University of Sheffield, United Kingdom.
  • Cox TJ; Acoustics Research Centre, University of Salford, United Kingdom.
  • Culling JF; School of Psychology, Cardiff University, United Kingdom.
  • Naylor G; Hearing Sciences - Scottish Section, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, United Kingdom.
  • Porter E; Hearing Sciences, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, United Kingdom.
  • Viveros-Muñoz R; School of Psychology, Cardiff University, United Kingdom.
Data Brief ; 41: 107951, 2022 Apr.
Article in En | MEDLINE | ID: mdl-35242933
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Data Brief Year: 2022 Document type: Article Affiliation country: United kingdom Country of publication: Netherlands

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Data Brief Year: 2022 Document type: Article Affiliation country: United kingdom Country of publication: Netherlands