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Automatic Speech-to-Phoneme Alignment of the Spoken British National Corpus

Abstract:
This poster describes the creation of an automatic word and phoneme alignment between the audio recordings of the Spoken British National Corpus (BNC) and their corresponding word-level transcriptions. The work presented here is part of the “Mining a Year of Speech” project which aim is to produce automatic speech-to-phoneme alignments of an approximately one year of audio recordings.The Spoken BNC recordings consist of unscripted, spontaneous speech conversations in different recording conditions, accents and background noises. The range of topics covers from radio programs to family conversations, council meetings or chemistry courses. The Spoken BNC was originally recorded on analogue cassette tapes between 1991 and 1994. These tapes have been recently-digitised by the British Library. The resulting dataset is composed of approximately 2,000 digital audio files with an average duration of 45 minutes and their associated word-level transcriptions. This poster describes the dataset, the automatic alignment process, the results obtained and the difficulties encountered.
Publication status:
Not published
Peer review status:
Not peer reviewed

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Institution:
University of Oxford
Research group:
Phonetics
Department:
Faculty of Linguistics, Philology and Phonetics
Role:
Author
More by this author
Institution:
University of Oxford
Research group:
Phonetics
Department:
Faculty of Linguistics, Philology and Phonetics
Role:
Author
More by this author
Institution:
University of Oxford
Research group:
Phonetics
Department:
Faculty of Linguistics, Philology and Phonetics
Role:
Author
More by this author
Institution:
University of Oxford
Research group:
Phonetics
Oxford college:
Wolfson College
Role:
Author


More from this funder
Funding agency for:
Baghai-Ravary, L
Kochanski, G
Coleman, J
Grant:
RES-062-23-2566
RES-062-23-1323
RES-062-23-2566
More from this funder
Funding agency for:
Grau Puerto, S
Coleman, J
Grant:
Digging into data
RES-062-23-2566


Publication date:
2011-01-01


UUID:
uuid:3652bbeb-24a6-4771-83cf-3f3aba260031
Deposit date:
2011-05-17
ARK identifier:

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