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MARSEC: A Machine-Readable Spoken English Corpus

Published online by Cambridge University Press:  06 February 2009

Peter Roach
Affiliation:
Department of Linguistic Science, University of Reading, Reading RG6 2AAU.K.
Gerry Knowles
Affiliation:
Department of Modern English Language and Linguistics, University of Lancaster, Bailrigg, Lancaster LA1 4YT, U.K..
Tamas Varadi
Affiliation:
Department of Modern English Language and Linguistics, University of Lancaster, Bailrigg, Lancaster LA1 4YT, U.K..
Simon Arnfield
Affiliation:
Department of Linguistic Science, University of Reading, Reading RG6 2AAU.K.

Extract

The purpose of this paper is to describe a new version of the Spoken English Corpus which will be of interest to phoneticians and other speech scientists. The Spoken English Corpus is a well-known collection of spoken-language texts that was collected and transcribed in the 1980's in a joint project involving IBM UK and the University of Lancaster (Alderson and Knowles forthcoming, Knowles and Taylor 1988). One valuable aspect of it is that the recorded material on which it was based is fairly freely available and the recording quality is generally good. At the time when the recordings were made, the idea of storing all the recorded material in digital form suitable for computer processing was of limited practicality. Although storage on digital tape was certainly feasible, this did not provide rapid computer access. The arrival of optical disk technology, with the possibility of storing very large amounts of digital data on a compact disk at relatively low cost, has brought about a revolution in ideas on database construction and use. It seemed to us that the recordings of the Spoken English Corpus (hereafter SEC) should now be converted into a form which would enable the user to gain access to the acoustic signal without the laborious business of winding through large amounts of tape. Once this was done, we should be able not only to listen to the recordings in a very convenient way, but also to carry out many automatic analyses of the material by computer.

Type
Article
Copyright
Copyright © Journal of the International Phonetic Association 1993

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