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Research Article

Perceptual and acoustic reliability estimates for the Speech Disorders Classification System (SDCS)

, , , , , , , , , & show all
Pages 825-846 | Received 09 Mar 2010, Accepted 17 Jun 2010, Published online: 10 Sep 2010
 

Abstract

A companion paper describes three extensions to a classification system for paediatric speech sound disorders termed the Speech Disorders Classification System (SDCS). The SDCS uses perceptual and acoustic data reduction methods to obtain information on a speaker's speech, prosody, and voice. The present paper provides reliability estimates for the two perceptual methods (narrow phonetic transcription; prosody-voice coding) and the acoustic analysis methods the SDCS uses to describe and classify a speaker's speech competence, precision, and stability. Speech samples from 10 speakers, five with significant motor speech disorder and five with typical speech, were re-measured to estimate intra-judge and inter-judge agreement for the perceptual and acoustic methods. Each of the speakers completed five speech tasks (total = 50 datasets), ranging in articulatory difficulty for the speakers, with consequences for the difficulty level of data reduction. Point-to-point percentage of agreement findings for the two perceptual methods were as high or higher than reported in literature reviews and from previous studies conducted within the laboratory. Percentage of agreement findings for the acoustics tasks of segmenting phonemes, editing fundamental frequency tracks, and estimating formants ranged from values in the mid 70% to 100%, with most estimates in the mid 80% to mid 90% range. Findings are interpreted as support for the perceptual and acoustic methods used in the SDCS to describe and classify speakers with speech sound disorders.

Acknowledgements

This research was supported by National Institute on Deafness and Other Communication Disorders Grant DC000496 and by a core grant to the Waisman Center from the National Institute of Child Health and Development (Grant HD03352). We thank the following colleagues for their contributions to this study: Chad Allen, Roger Brown, Peter Flipsen, Jr., Katherina Hauner, Jessica Hersh, Joan Kwiatkowski, Sara Misurelli, Rebecca Rutkowski, and Sonja Wilson.

Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

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